Cognitive functions in typically developing children with varied socioeconomic status and the impact of training on executive functions and reading skills

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UNIVERSIDADE FEDERAL DO RIO GRANDE DO NORTE CENTRO DE CIÊNCIAS HUMANAS, LETRAS E ARTES

DEPARTAMENTO DE LETRAS

PROGRAMA DE PÓS-GRADUAÇÃO EM ESTUDOS DA LINGUAGEM

RENATA CALLIPO FUJII

COGNITIVE FUNCTIONS IN TYPICALLY DEVELOPING CHILDREN WITH VARIED SOCIOECONOMIC STATUS AND THE IMPACT OF TRAINING ON

EXECUTIVE FUNCTIONS AND READING SKILLS

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Tese apresentada ao Programa de Pós-graduação em Estudos da Linguagem da Universidade Federal do Rio Grande do Norte, para a obtenção do grau de Doutor em Letras

PhD Candidate: Renata Callipo Fujii Advisor: Dr. Janaina Weissheimer

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Tese submetida à comissão examinadora designada pelo colegiado do Programa de Pós-Graduação em Estudos da Linguagem da Universidade Federal do Rio Grande do Norte como requisito para obtenção do grau de Doutor em Letras na área de concentração de Linguística Aplicada.

Natal, July 20th 2020.

BANCA EXAMINADORA

__________________________________________________ Professora Doutora Janaína Weissheimer

Orientadora/Presidente

__________________________________________________

Professor Doutor Augusto Buchweitz

Membro Externo

__________________________________________________ Professora Doutora Natália Bezerra Mota

Membro Externo

__________________________________________________ Professora Doutora Ingrid Finger

Membro Externo

__________________________________________________ Professora Doutora Mahayana Godoy

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AGRADECIMENTOS

À minha professora orientadora Janaína por ter acreditado em mim e por ter dado um sentido único à missão de orientar. Sou grata pela sua paciência, dedicação e parceria; por me guiar e por se fazer presente de maneira incondicional. São raras as pessoas assim nesse mundo.

Ao Projeto ACERTA, sem o qual minha pesquisa não existiria. Aos mentores Augusto e Sidarta: sou grata pelo apoio e amizade. Em especial, ao acolhimento e ensinamentos da Natália que muito me ajudou em momentos cruciais nessa jornada. E minha gratidão à Mahayana que contribuiu imensamente para esse trabalho com seu rico feedback no momento da minha qualificação.

À CAPES pela bolsa PGCI que me possibilitou a concretização de um sonho: passar um ano na YALE University. Ao Kenneth Pugh pelo acolhimento em seu laboratório e pelos ensinamentos que vão além daqueles da vida acadêmica.

To the person who supported me and believed in this study: Susanne Jaeggi, I am very grateful for all your encouragement. This journey would not have been possible without you and everyone at the Working Memory and Plasticity Lab at UCI Irvine.

Aos colegas internacionais: Luca, Tian e Mark – pessoas brilhantes e humildes com quem tive e privilégio de conviver e aprender imensamente.

Aos queridos amigos: Leo, Érica, Ednny, Juliana, Talita e Alessandra. Sei o quanto realmente compartilharam da minha felicidade durante todo esse tempo de estudo e pesquisa. Agradeço cada sorriso, cada abraço e palavra de incentivo. Vocês são muito especiais.

Às Diretoras do colégio CEI, Ana Flávia e Cristine, que sempre confiaram no meu trabalho e me permitiram assistir às aulas na universidade e realizar a minha coleta, sem que eu me sentisse culpada por não estar presente na escola nesses momentos. Obrigada pelo incentivo incondicional.

Aos professores das turmas com as quais trabalhei. Gratidão imensa. Finalmente agradeço a todos os estudantes que participaram dessa pesquisa, sem essa cooperação, não existiria trabalho algum.

Aos meus pais pelo carinho, pelas conversas e desabafos. Sou eternamente grata por terem me ensinado que a perseverança é o caminho do sucesso.

Aos meus filhos: Aniara, Isadora e Heitor. Sem vocês, nada disso teria sentido. Vocês são a razão do meu viver. Obrigada por existirem.

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ABSTRACT

Reading comprehension refers to a complex cognitive ability that draws on a variety of language skills and processes. Executive Functions play an important role in complex cognition and are essential mental processes needed for language processing. Thus, based on research about Executive Functions, Language Processing and Socioeconomic Status, this study investigated: (i) the relationships between EF skills, SES and measures of achievement and cognitive abilities; (ii) the effectiveness of a gaming intervention that directly and specifically taxes the EF system on the same set of skills (near transfer); (iii) the effectiveness of a gaming intervention that taxes the EF system on reading abilities (far transfer). Overall, 122 3rd_{and 4}th_{grade students from}

private and public schools in Natal / RN took part in this study. They were randomly split into two groups. One group trained on Android tablets games which taxed Executive Function skills. The other group (active control) trained on Android tablet games which minimally taxed Executive Function skills. Paper and pencil tasks were also administered to assess reading comprehension and attention. Results indicated that there is a very close relation between EF skills, and scholastic outcomes. Findings also pointed out that children’s updating feature of working memory and their selective

attention improves after training. The ability to read pseudowords also improves after training, which signals an important contribution of the intervention in ameliorating decoding skills and language acquisition processes. The main contributions of this study are that it might offer insights for pedagogical purposes (adjusting EF training to best fit each specific group of students, therefore aiding teachers); as well as serve as guideline for future educational policies.

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RESUMO

FUNÇÕES EXECUTIVAS EM CRIANÇAS COM DESENVOLVIMENTO TÍPICO EM NÍVEIS SOCIOECONÔMICOS VARIADOS E O IMPACTO DO

TREINO SOBRE A FUNÇÕES EXECUTIVAS E A HABILIDADES DE LEITURA

A compreensão de leitura pode ser entendida como uma habilidade cognitiva complexa que demanda uma diversidade de competências e processos linguísticos. Funções Executivas desempenham um importante papel para a cognição e para o processamento da linguagem. Desta feita, pautado em estudos sobre Funções Executivas, Processamento da Leitura e Condições Socioeconômicas, o presente estudo investigou: (i) as relações entre Funções Executivas, Condições Socioeconômicas e medidas de habilidades cognitivas; (ii) a eficácia de uma intervenção que fez uso de jogos que diretamente e especificamente requerem o uso do sistema de Funções Executivas sobre as mesmas funções (transferência direta); (iii) a eficácia de uma intervenção que fez uso de jogos que diretamente e especificamente requerem o uso do sistema de Funções Executivas sobre o processamento da leitura (transferência indireta). Participaram deste estudo ao todo 122 alunos de 3o e 4os anos da rede privada e pública das escolas de Natal/RN. Os participantes foram randomicamente divididos em 2 grupos. Um deles treinou com jogos que ativam funções executivas (experimental). O outro grupo (controle ativo) treinou com jogos que não ativam Funções Executivas. Testes escritos também foram administrados com o intuito de mensurar o processamento da leitura bem como a atenção dos alunos. Os resultados indicaram que existem relações íntimas entre Funções Executivas e desempenho escolar. Os dados sugerem que funções executivas e atenção seletiva melhoram consideravelmente após o treino. A habilidade de leitura de pseudopalavras também melhorou depois do treino, especificamente em relação à fluência de decodificação, o que sinaliza para uma importante contribuição da intervenção em trazer benefícios para os processos de aquisição de linguagem e leitura. As principais contribuições do presente estudo são os caminhos que ele pode oferecer para propósitos pedagógicos (ajustando treinos de funções executivas para melhor se encaixar em grupos específicos de alunos), portanto, servindo de ajuda para professores, como também servir de guia para políticas públicas educacionais.

Palavras chave: Funções Executivas. Leitura. Condições Socioeconômicas.

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LIST OF FIGURES

Figure 1 Working Memory Model ……….20

Figure 2 IDEB Scores ………..41

Figure 3 Repetition rates - Public vs Private Schools ……….41

Figure 4 Age-grade distortion rates ………...42

Figure 5 Research design ………...46

Figure 6 n-Back screen ………...47

Figure 7 Touch base screen ………...48

Figure 8 Dog game screen ………..49

Figure 9 Monkey game screen ………...49

Figure 10 d2 Test - front page ………..50

Figure 11 d2 Test Backpage ……….51

Figure 12 Match Quest screen ………..52

Figure 13 Recall All screen ………...53

Figure 14 Clouds game screen ……….55

Figure 15 Clouds game screen ………56.

Figure 16 Eagle Eye game screen ………...57

Figure 17 Charm King game screen ………61

Figure 18 Find the differences game screen ………..62

Figure 19 n-Back performance …. ………...70

Figure 20 d2 performance ……… ………71

Figure 21 Dogs and Monkeys and Touch Base performance ……….72

Figure 22 Pseudoword time performance ……..……….76

Figure 23 Pseudoword performance accuracy ..………77

Figure 24 Reading speed and reading comprehension performance….……...78.

Figure 25 Average Training Curves for Match Quest ..……….82

Figure 26 Average Training Curves for Recall All ……….82

Figure 27 Average Training Curves for Clouds ……….83

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LIST OF TABLES

Table 1 Demographic data ………..43

Table 2 Attendance data by School for the testing days ………44

Table 3 Recall all themes and characters ……….54

Table 4 Games and EF skills ………55

Table 5 Baseline assessments for Executive Functions and Reading Tasks Public x Private Schools……….65

Table 6 Baseline assessments - Experimental and Control Groups …………67

Table 7 Descriptive data and effect sizes for the experimental group ……….69

Table 8 Descriptive data and effect sizes for the control group ………69

Table 9 Descriptive data and effect sizes for the experimental group ……….75

Table 10 Descriptive data and effect sizes for the control group ………..75

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LIST OF APPENDICES

Appendix A1 Consent form (TCLE) sent to participants/parents ………98

Appendix A 2 Ethics Committee form ………100

Appendix A3 Non - disclosure Agreement ………...100

Appendix A 4 Ethics Committee Approval ………100

Appendix A5 SES Questionnaire ………106

Appendix B1 d2 test of Attention ………111

Appendix B2 d2 Scoring Manual ………..………..112

Appendix B3 Text: “Bebe elefante”……….113

Appendix B4 Reading comprehension ctivity for “Bebe elefante”…… ……….114

Appendix B5 Text: “O Camaleao” ………..117

Appendix B6 Reading comprehension activity for “O Camaleao” ……….118

Appendix B7 Text: “A Girafa ………120

Appendix B8 - Reading comprehension activity for “A Girafa”………...121

Appendix B9 Text: “As Lhamas” ……….124

Appendix B10 Reading comprehension activity for “As Lhamas” …………...125

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TABLE OF CONTENTS

INTRODUCTION ... 13

1.1 BACKGROUND TO THE STUDY ... 13

1.2 STATEMENT OF THE PURPOSE... 15

1.3 SIGNIFICANCE OF THE STUDY ... 15

1.4 ORGANIZATION OF THE DISSERTATION ... 17

2. REVIEW OF THE LITERATURE... 18

2.1 EXECUTIVE FUNCTIONS AND CHILD DEVELOPMENT ... 18

2.1.1 Components of Executive Function ... 19

2.1.2 Executive Functions and Reading ... 22

2.2 SOCIOECONOMIC STATUS AND THE DEVELOPING BRAIN ... 24

2.2.1 Defining Socioeconomic Status ... 24

2.2.2 Empirical Studies on Socioeconomic Status, Executive Functions, and scholastic achievement ... 27

2.3 TRAINING ON EXECUTIVE FUNCTIONS ... 31

2.3.1 What is training? ... 31

2.3.2 Empirical Studies on EF Training ... 33

3 RESEARCH DESIGN ... 38

3.1 Type of Study... 38

3.2 Objectives and Hypotheses ... 38

3.2.1 General Objective... 38

3.2.2 Specific Objectives ... 39

3.2.3 Hypotheses ... 39

3.3 Methods ... 39

3.3.1 Context and Participants ... 40

3.3.1.1The Natal and Rio Grande do Norte Context ... 40

3.3.1.2 Participants ... 43

3.3.2 Instruments and Procedures... 44

3.3.3 Tablet Games and inhibitory control test ... 46

3.3.3.1 Pre-test and Posttest Assessment ... 47

3.3.3.1.1 Spatial Working Memory: N-Back ... 47

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3.3.3.1.3 Inhibitory control: Dogs and Monkeys Game ... 48

3.3.3.1.4 Inhibitory control and Sustained Attention: d2 Test ... 50

3.3.3.2 Executive Function Training Games ... 51

3.3.3.2.1 Match Quest ... 52

3.3.3.2.2 Recall All ... 53

3.3.3.3 Active Control Games ... 55

3.3.3.3.1 Clouds ... 55

3.3.3.3.2 Eagle Eye ... 56

3.3.4 Reading Skills ... 57

3.3.4.1 Words and Pseudo words... 57

3.3.4.2 Reading Comprehension Task ... 58

3.5 Pilot Study ... 59

4. PRESENTATION, ANALYSES, AND INTERPRETATION OF DATA ... 63

4.1 Presentation... 63

4.2 Analyses and Discussion ... 64

4.2.1 The relations between EF skills, SES and measures of scholastic achievement and cognitive abilities at baseline... 64

4.2.2 The effectiveness of a gaming intervention on the same set of skills (near transfer). ... 68

4.2.3. The effectiveness of a gaming intervention that taxes the EF system on scholastic outcomes (far transfer). ... 75

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INTRODUCTION

1.1 BACKGROUND TO THE STUDY

As an educator, I have always wondered why some children seem to achieve better and faster outcomes. Of course, working at schools, we always hear this saying that is sometimes repeated like a mantra: “Children learn at their own pace”. That is also what we tell parents when their children fall behind, and as teachers, we sometimes do not quite know how to help these students.

Moved by a desire to become a better teacher, and better understand how children learn, I decided to take a Specialization Course on Second Language Acquisition; and a few years ago, I began my studies as a Postgraduate student. I set out to investigate the field of Working Memory, and, at the time, I chose to examine the possible connections between Working Memory and reading abilities (because, after all, my primary field of work is on Psycholinguistics as a sub area of Applied Linguistics). As a research member of Project ACERTA 1_{, I recruited 45 3rd grade students, and conducted my} study. Data collection was carried out in public-schools located in the northeast of Brazil. This specific scenario brought a many number of challenges to the accomplishment of this research. Most of the schools did not have a library, and a quiet place to collect data was hard to find. Children presented difficulties in understanding the instructions given for each task and, in general, presented low scores on their reading standardized tests (some could not read nor write and were much older than their peers/per school grade). For my master’s study, Working Memory capacity was assessed using tasks from the AWMA assessment (Automated Working Memory Assessment); and reading skills were measured using a standardized test applied to all Brazilian students in public schools (from 2nd_{to 4}th_{grade). Results indicated that reading skills within}

children at risk of reading disabilities were directly linked to deficits in working memory capacity, especially with regards to the phonological component (Fujii,

1 _{Project ACERTA was conducted and coordinated by Dr. Augusto Buchweitz. Together with two}

other Brain Institutes in Brazil, the Brain Institute in the city of Natal/RN investigated children at risk for reading difficulties (in public schools) and aimed at building a bridge between neuroscience and education.

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R. C., 2017). It was also evident that the participants with poor working memory showed more difficulties in the specific reading tasks that demanded interpretation skills.

Throughout this journey, the more I studied about Working Memory, the more I realized it was a skill that permeated greater and more diverse aspects of people’s lives. Working Memory was not only crucial for school readiness and success, but also for the accomplishment of social and professional goals. Not only that, but Working Memory was part of a larger set of skills, called Executive Functions (EF).

Since the very beginning of my postgraduate studies, I had heard and read about the possibility of training Executive Functions, and the considerable impacts this could cause on other abilities connected to Executive Function skills, such as reading, for example. Furthermore, the previous data collection at public schools raised my interest in the gap between low and high achieving students; and whether Socioeconomic Status (SES) might play a role in learning abilities. In the year 2016, I attended the LA School - Latin American School for Education, Cognitive and Neural Sciences and had the opportunity to meet Dr. Susanne Jaeggi and Dr. Sebastian Lipina. Dr. Jaeggi is the principal investigator in the Working Memory and Plasticity Laboratory at the University of California – Irvine. The Plasticity Lab conducts many studies mainly focusing on the investigation of cognitive training and transfer. Dr. Sebastian Lipina focuses his research on the impact of poverty on development, cognition, and the brain. At this very important event, a beautiful collaboration was born, and together, Dr Jaeggi and I set out to investigate the effects of SES in a Game-based EF intervention in children from the Northeast of Brazil, thus the topic of my dissertation.

In the year 2018 I had the amazing opportunity to spend 11 months at Haskins Laboratories – affiliated to Yale University in Connecticut. Haskins Lab – administered by Dr. Kenneth Pugh (President and Director of Research) produces research on the enhancement and better understanding of speech perception and production, reading and reading disabilities, and human communications. As an apprentice at the lab I was able to study and manipulate cutting edge technology and brain imaging tools which investigate how children learn to read. In addition, the post docs at the lab and Ken (as everyone called

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him) himself were key to helping me interpret data from this present study. The entire experience was a phenomenal one as it enabled me to meet people with so many different fields of expertise and thus form a multidisciplinary group of colleagues who contributed in many ways to this research.

1.2 STATEMENT OF THE PURPOSE

Assuming EF skills are closely connected to scholastic outcomes, the objective of this study was to investigate the relationships between EF, SES and measures of scholastic achievement and cognitive abilities; as well as to analyze if/how SES might mediate the impact of far and near training of EF using a game-based intervention. The objectives posed in this study were the following: (i) to examine the relationships between EF skills, SES and measures of achievement and cognitive abilities; (ii) to examine the effectiveness of a gaming intervention that directly and specifically taxes the EF system on the same set of skills (near transfer); (iii) to examine the effectiveness of a gaming intervention that taxes the EF system on scholastic outcomes - reading abilities (far transfer). And, the hypotheses: (i) EF skills and SES will have a close connection to reading measures; low-SES children will show deficits in EF skills as well as in scholastic outcomes, when compared to their high-SES peers; (ii) the gaming intervention will ameliorate the trained skills (near transfer will occur) (iii) the gaming intervention will ameliorate the non-trained skills (far transfer will occur to some extent, at least).

1.3 SIGNIFICANCE OF THE STUDY

As far as educational research goes, there seems to be a very strong paradox underlying such studies in the sense that factors which impact learning and behavior can be easily identified; although it is not so easy to apply this knowledge and use it to inform educational practices. In other words, it can be very difficult to translate theories and measurements into daily educational practices that can be helpful to guide teachers. In the field of EFs research, for example, identifying children with EFs difficulties is not such a complex task, but it can be very problematic and not as simple to devise effective forms of

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intervention that can minimize educational gaps (resulting from EFs deficits). Furthermore, even though there is evidence showing the close relations between SES and scholastic outcomes, understanding what drives this relationship and the mechanisms that underlie such associations (for example aspects connected to the regulation of stress or the quality of parenting environments) is still an important task. A clearer insight on the experience of poverty and the changes it might cause in the nervous system can indicate further evidence for the design of proper interventions and policies, as well as for educational practices.

It is, indeed, high time for evidence-based education; although, as mentioned previously, educational research has remained distant from the classrooms. Building a bridge between scientific evidence and education, as argued by Sigman et. al (2014), is not only necessary, but also urgent. The authors state that neuroscience and cognitive psychology should work in synergy aiming at providing complementary tools for the better understanding of the mind and the improvement of education. That is to say that education should inspire research and contribute to unique problems and novel experimental conditions (Sigman et. al, 2014). In addition, educational practices may come to benefit from understanding the processes involved in the act of learning from a more scientific perspective (Howard-Jones et. al, 2016).

This study adds to the body of Executive Functions (EFs) research and Socioeconomic Status (SES) research, more specifically to the field of EF training, by reason of the following issues. First, many studies have investigated the effects of EF training on children (Goldin et al. 2014; Segretin et al. 2014; Loosli et al. 2011; Thorell et al. 2009). Nonetheless, to the best of my knowledge, no study in Brazil has administered tablet games (specifically tailored for the age range of the participants) as a tool to train EFs skills; also, no study in the country has specifically tested EF interventions in high vs low SES children. Second, considering that research in EFs and SES has focused mainly on children from other countries, another contribution of this study is the fact that it was conducted with Brazilian children from public and private schools in the city of Natal/RN. Thus, this study may yield important information about this specific population (shedding more light on the relation between EFs, training, SES and scholastic outcomes). The study might also offer insights for

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pedagogical purposes (adjusting EF training to best fit each specific group of students, therefore aiding teachers); as well as serve as guideline for future educational policies. The more we understand about SES and its impacts on learning, “the more rationally we can design programs for prevention and remediation” (Hackman & Farah, 2008).

1.4 ORGANIZATION OF THE DISSERTATION

Following this Introduction, chapter 2 presents the theoretical background that served as a guide to this research: (1) Executive Functions and child development, the main area in which this study is grounded; (2) The theoretical work and empirical studies on Socioeconomic Status and its relationships with the developing brain; and (3) Theoretical work and empirical studies on training of executive functions.

Chapter 3 presents the description of the methods employed in this study and it also includes: the general and specific objectives, hypotheses; as well as information about the participants and setting, the instruments and procedures for data collection and data analyses.

Chapter 4 brings the results, which are analyzed and discussed in accordance to the research questions and hypotheses proposed in Chapter 3 and considering the review of the literature presented in Chapter 2.

Lastly, research findings are summarized and reflected upon in the Conclusions section. Limitations of the study are discussed as well as pedagogical implications.

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2. REVIEW OF THE LITERATURE

This chapter encompasses the theoretical background and rationale for the present study and it is divided into three sections: (1) Executive Functions and child development, which defines each core EF and describes how these skills are assessed in our study; (2) Socioeconomic Status and its relations with the developing brain, which defines SES and reviews the main empirical research in the field, related to this study; (3) Training of Executive Functions, which discusses the effectiveness of training executive functions in children and reviews empirical research as well.

2.1 EXECUTIVE FUNCTIONS AND CHILD DEVELOPMENT

Executive Functions (EF) refer to a set of neurocognitive skills which are indispensable for mental and physical health, school readiness and success; as well as psychological, social, and cognitive development (Diamond, 2013). EFs play an important role in complex cognition and are essential mental processes needed for reasoning, planning, goal-oriented problem solving, memory and language processing (Diamond, 2013; Carlson et al. 2013).

EFs depend heavily upon neural networks in the prefrontal cortex, one of the slowest developing brain areas (Miyake & Friedman, 2012; Carlson et al., 2013; Zelazo & Muller, 2002; Garon et al., 2008). EFs emerge early (around the end of the first year of life) and continue to develop rapidly during the preschool years (with important changes occurring between about 2 and 5 years of age) into adulthood (Carlson et al., 2013; Zelazo & Muller, 2002).

EFs can be understood as a unitary construct which is influenced by development and experience and may vary as a function of factors such as socioeconomic status, language, culture, caregiving, sleep, and gene-environment interactions (Carlson et al. 2013)

According to a very influential taxonomy, there are three basic EFs: updating, inhibition and shifting (Diamond, 2013; Hofmann 2012; Miyake et. al. 2000). Updating refers to the ability to keep information in mind in an active state, in such a way that it can be quickly retrieved; in other words, the ability to process information while holding it in mind (Diamond 2013; Hofmann 2012).

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Updating is closely associated to the construct of working memory. Inhibition involves the ability to "deliberately inhibit dominant, automatic, or prepotent responses when necessary" (Miyake et al., 2000, p.57). Shifting, also referred to as ‘attention switching’ or ‘task switching’, concerns the ability to shift back and forth between multiple tasks, mental sets or operations (Monsell, 2003).

Impairments in EFs are closely connected to forgetting and inattentive behavior; high levels of distractibility; difficulties in monitoring classroom work; and difficulties in generating new solutions to problems (Alloway et al., 2008a). Children with deficits in EF skills usually present an extremely high risk of making poor academic progress and struggle in learning measures (vocabulary, reading and math).

For the purposes of this study, we do not intend to provide an exhaustive account of EFs, but rather a review of the main studies in the area following in section 2.1.2.

2.1.1 Components of Executive Function

The first component of the tripartite structure identified by Miyake and colleagues (2002) is updating. As mentioned previously, updating is closely related to the construct of Working Memory.

A three-component model of Working Memory was proposed by Baddeley and Hitch in the year 1974; thus, providing a framework for conceptualizing the role of temporary storage of information in the performance of ongoing complex cognitive tasks. This model was a development of early models of short-term memory, but it differed from previous ones such as those of Broadbent (Broadbent, 1958) and Atkinson and Shiffrin (Atkinson & Shiffrin, 1968) in two ways. First, the concept of a unitary temporary store was abandoned in favor of a multicomponent system, and second, the model highlighted the function of the system in complex cognition, rather than emphasizing memory per se (Baddeley, 2000).

According to this model (Fig 1), the central executive is an attentional controller which is supported by two subsidiary “slave” systems, the phonological loop, responsible for providing temporary storage of verbal and acoustic material, and the visuospatial sketchpad, responsible for maintaining

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and manipulating visual and spatial representations. The two systems form active stores which can combine information from sensory input and from the central executive. Consequently, a memory trace in the phonological store can either derive from an auditory input, or from the sub vocalization of a visually presented item such as a letter (Baddeley, 2000).

Figure 1

Working Memory Model

Figure 1 shows the central executive functions as an attentional controller. Two subsidiary systems support the central executive: the phonological loop and the visuospatial sketchpad. Source: Baddeley (2000).

Importantly, the updating function requires the dynamic manipulation of working memory representations and goes far beyond passively storing information (Lehto, 1996; Morris & Jones, 1990 as cited in Miyake, 2000). Updating is often investigated using running memory or n-back tasks. In the present study, we used tablet games which presented the n-back task in a videogame like format.

The second component of the tripartite structure is inhibition, also referred to as inhibitory control. This executive function concerns the ability to deliberately inhibit automatic, dominant, or prepotent responses when necessary; as well as the ability to resist external stimuli and strong behavioral tendencies (Miyake et al., 2000; Davidson et al., 2006). Inhibitory control can also be described as the ability to control one’s attention, thoughts, behavior

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and/or emotion to do what is more appropriate and needed, rather than give in to temptation (Diamond, 2013).

The inhibition of distractors is responsible for enabling selective and sustained attention (Davidson et al., 2006). For young children, inhibitory control can be disproportionately difficult. For example, results from a study conducted by Davidson et al. (2006) suggest that the younger the children, the harder it was for them to mobilize inhibition skills either at the level of attention (showing difficulties in disregarding an irrelevant aspect of a stimulus); and also at the level of response (difficulties in overriding the prepotent tendency to respond to the stimulus in the same way). In the present study, we used the d2 test to assess inhibitory control. The d2 test aims at measuring processing speed and inhibitory control while processing a series of similar visual stimuli.

The third core EF is shifting, also referred to as cognitive flexibility. Shifting concerns, the ability to change perspectives, either spatially or interpersonally; it means shifting back and forth between multiple tasks and it involves being flexible to adjust to changed demands or priorities. Shifting comes much later in development and builds on updating and inhibition In a changing world, shifting – or being able to see things in new or different ways - is essential for adaptability and creativity (Diamond, 2013; Miyake et al., 2000; Davidson et al., 2006).

Shifting can be very difficult, and the reason is because it is something that cannot be done “on automatic”; top-down executive control is required and working memory and inhibition are also taxed (newly-relevant rules and stimulus–response relations must be activated, and the previously-relevant ones suppressed). Shifting is usually investigated using task-switching paradigms which target the ability to flexibly shift from one mindset to another (Davidson et al. 2006) For our study, we assessed this skill using a videogame -like tablet game which taxed the ability to switch tasks.

Next, we will address the relations between Executive Functions and reading comprehension skills, since these two constructs are closely intertwined in the case of children in elementary school as EFs are recruited when children are reading.

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2.1.2 Executive Functions and Reading

Text comprehension refers to a complex cognitive ability that draws on a variety of language skills and processes. Word-level skills such as word-reading efficiency and vocabulary knowledge, and sentence-level skills such as knowledge of grammatical structure - both play an important role in reading comprehension (Cain, Oakhill, & Bryant, 2004; Carretti et al., 2014).

In addition, important higher order text-processing skills, such as integration and inference, reading monitoring and knowledge of story structure, are also crucial for the construction of an integrated and coherent model of a text (Gernsbacher, 1990; Cain, Oakhill, & Bryant, 2004).

Text comprehension involves forming a meaning-based representation of the text – often called a situational model (Kintch & Vandijk, 1978, Gernsbacher, 1990; Cain, Oakhill, & Bryant, 2004). To properly integrate information from a text, the reader relies on processes which require that relevant information, either from the text or world knowledge, be available and accessible. For this, Working Memory will serve as a buffer enabling the reader to engage in reading while maintaining some piece of information; but also merging that information with previous knowledge – in other words, actively processing incoming information (Cain, Oakhill, & Bryant, 2004; Carretti et al., 2009).

It is well established in the literature that Working Memory is strongly related to reading comprehension ability. For example, Working Memory capacity is correlated with university students` performance on standardized tests of reading skills (Daneman & Carpenter, 1980). More than that, Working Memory capacity is also related to important skills that contribute to text comprehension, such as memory for facts, inference of unknown word meanings from context and resolution of pronouns (Daneman & Carpenter, 1980; Daneman & Green, 1986; Cain, Oakhill, & Bryant, 2004).

A growing body of research has investigated the relations between Executive Functions and reading comprehension. Carretti et al. (2005), for example, examined the relation between text comprehension and success in a Working Memory updating task. Findings confirmed that reading-disabled children's deficiencies were associated with a specific difficulty in the Working Memory updating process: the ability to control for information that is no longer

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relevant. Participants in this study were poor and good comprehenders, ages 8-11 years. Thus, according to the results, Working Memory seems critical in text comprehension and this relation is probably mediated by inhibition.

Furthermore, a longitudinal study conducted by Cain et al. (2004) investigated the relations between Working Memory capacity and reading comprehension skills in children aged 8, 9 and 11 years. Children were assessed in their reading abilities, vocabulary, and verbal skills. Two Working Memory tasks were administered (sentence-span and digit Working Memory). Findings showed that Working Memory capacity and comprehension skills explained a unique variance in reading comprehension, after the contributions of word-reading and verbal and vocabulary ability (lower level skills) were controlled for.

Carretti et al. (2009) report on a meta-analysis investigating the role of Working Memory in explaining specific reading comprehension difficulties. They examine the relevance of several Working Memory measures used to distinguish between the performance of poor and good comprehenders in terms of the modality of the Working Memory task. They also investigate the involvement of controlled attention required by such tasks. Their findings demonstrate that poor and good comprehenders are best distinguished by memory tasks that require the processing of verbal information and tasks which are demanding in terms of attentional control. This suggests that both general factors as well as domain-specific factors of Working Memory contribute to text comprehension performance.

Another study regarding Working Memory and reading comprehension difficulties was one conducted by Gathercole et al. (2006). A sample of 46 children with reading disabilities (aged between 6 and 11 years) was tested on measures of verbal and visuospatial short-term memory, complex memory, phonological processing, IQ, language, literacy, and mathematics. Researchers found strong associations between the severity of reading difficulties and Working Memory, language, and phonological processing abilities. Results suggest that working memory may represent an important constraint on the development of knowledge and skills which are key domains of reading.

Regardless of the large body of research focused on Executive Functions and its close relation to reading difficulties, problems involving deficits in EFs

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can often be misinterpreted as children’s lack of motivation and effort; and low Executive Function skills can go undetected in the classroom. As mentioned previously, research findings are usually not easily translated into classroom practices.

Overall, the links between Executive Functions and reading are robust. There is also evidence that Executive Function skills may play a key role in the achievement gap between children from low and high Socioeconomic backgrounds (Zelazo et al., 2016). Next, the connections between Executive Functions and Socioeconomic Status are presented and discussed.

2.2 SOCIOECONOMIC STATUS AND THE DEVELOPING BRAIN

In this section, we present the definition of Socioeconomic Status adopted in this study, along with a review of the recent studies conducted in the field. We also discuss SES and its relations with brain development.

2.2.1 Defining Socioeconomic Status

Brain development and cognitive functions are influenced by a very complex interplay between environmental and genetic factors and can also be significantly affected by Socioeconomic Status - SES (Noble et al., 2007).

Socioeconomic Status (SES) is a very complex social phenomena, usually studied in the fields of sociology and developmental psychology. For most authors, SES is a multidimensional construct and refers to an individual's access to economic and social resources, together with the social positioning, benefits, prestige and power that stem from these resources (Brito & Noble, 2014; Duncan & Magnuson, 2012; Hackman & Farah, 2008).

Only in recent years has SES been incorporated into a growing body of neuroscience and educational studies on children; and has become a topic of research (Duncan & Magnuson, 2012; Farah, 2017). SES can sometimes be thought of as too vague a construct, mainly because it combines several components - economic, educational, and occupational. And, for some authors,

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SES encompasses other components, such as cultural differences in habits, tastes, linguistic patterns, preferences, and worldviews (Duncan & Magnuson, 2012).

Thus, not only does SES combine several components, but it is argued that each of its components can affect cognitive development in different ways. The correlations between SES constituents and children’s cognitive functioning are often very substantial, although the causal role played by each of them is not yet clear (Duncan & Magnuson, 2012).

Therefore, as researchers, one of the most challenging tasks we are faced with is to define what we mean by SES. Well, when the question “What is SES?” is posed, a non-technical response to it might occur. This intuitive account stems from our common understanding of “best off” and “worst off” individuals, meaning that “better off” individuals have more material and also non-material resources – such as education, prestige deriving from occupation and better neighborhood quality (Farah, 2017).

According to this dimension of SES, the material and non-material aspects of the construct tend to correlate with each other. Therefore, we could say that the more education one has, the higher the income, and consequently, the higher the chances to have access to a better neighborhood and to a more prestigious life. Although this correlation seems evident, it is not perfect at all. “SES corresponds to a complex bundle of social and economic factors that are generally but imperfectly correlated” (Farah, 2017).

Defining SES can be a very difficult task given its highly complex and imprecise nature. Nonetheless, measuring SES can also be very complicated and controversial. In fact, SES is measured in a wide variety of ways among different researchers.

Because it can be very challenging to obtain a precise income data from research participants (people have difficulties recalling their wages and may have various other sources of income: help from family, tips, bonuses), SES is often measured in terms of social factors. The most common indicators are educational attainment and occupational status; neighborhood characteristics can also be considered, in terms of the percentage of population living below the poverty line - this can be assessed using government database (Hackman & Farah, 2008; Farah, 2017). Although it may not be ideal to operationalize SES

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by taking into consideration just one or two measures, it is the most common approach in neuroscience research” (Farah, 2017). Nonetheless, some scholars may choose not to use a direct assessment of the components of SES, but will use proxy measures such as family structure, free or reduced lunch program status, and home ownership. Other attempts might include measuring SES subjectively – this means asking individuals where they see themselves on the ladder of social status (Duncan & Magnuson, 2012).

The several approaches to measuring SES may have underlying assumptions which can be very questionable. First, the belief that there is a strong correlation between the SES components. As mentioned previously, although the correlations among income, education and occupational status tend to be very high, they are far from perfect. Second, the assumption that SES can be considered fairly stable throughout childhood and adolescence. This is not true for income, for example, as it can shift dramatically depending on government policy, taxes, changes in parental employment and family structure. Third, the idea that different SES components will affect children in the same way, or in a uniform manner. The causal role played by each SES component is still not very clear, and “it is likely that the processes by which each of these components affect cognitive development differ as well” (Duncan & Magnuson, 2012).

So, why consider SES when conducting research, given the high complexity of the concept and the extreme difficulty to measure its many components? Well, the reason is because SES has been shown to be predictive of an impressive broad range of many life outcomes, such as physical health, lifespan, mental health, and school readiness. In addition, SES is strongly associated to cognitive ability and school outcomes; and is an important predictor of neurocognitive performance, especially of language and executive functions (Hackman & Farah, 2008).

In the present study, SES will be measured through the following components: parental education (% of high school completion), whether families receive government support or not, and if the household has basic home appliances These components will be combined and scored accordingly; and are presented in the Methods section. The complete SES questionnaire can be accessed in the Appendix Section (APPENDIX A5). We do not assume that all

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measures of SES are equally predictive of EFs and scholastic achievements; rather, we consider SES as a moderator. Studies have reported that when performance is modulated by SES, this does not happen in a uniform manner across ages, nor does it affect all areas of behavior in the same way (Noble et al, 2005; Farah et al, 2006; Lipina & Posner, 2012). In other words, ‘poverty does not necessarily generate homogeneous and continuous changes in neurocognitive processing’ (Lipina & Posner, 2012).

Finally, we point out that poverty, parental occupation and educational attainment are not the causes of potential detrimental effects on cognition in low SES children, but rather the many consequences that stem from those, such as: stress, violence, exposure to toxins, poor schooling, lack of food, lack of proper medical care, among many others.

In the following section, we highlight empirical studies that focus on the influence of SES in brain development and its close relations to Executive Functions, school readiness and success.

2.2.2 Empirical Studies on Socioeconomic Status, Executive Functions, and scholastic achievement

In this section, empirical studies on SES, EFs and scholastic achievement are reviewed. In Lupien et al. (2001), a cross-sectional experimental design was used, with six age groups (ranging from 6 to 16 years old) and two categories of SES (307 children of low and high SES). Schools were chosen for this study with the help of census data and according to the SES levels of the neighborhoods in which they are located. Criterion for SES used parent’s income and education level. The study took place in Montreal, and the neuropsychological session lasted for about 1hr and was performed in the classroom, using a group-testing method. Declarative memory tests, non-declarative tests and selective attention tests were applied. Results obtained in this study revealed significant developmental SES differences in cortisol levels during childhood, which tended to equalize during youth. According to the authors, SES differences in basal cortisol levels do not impact on cognitive performance on tests of memory and linguistic abilities in this population. The

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only SES difference to emerge about cognitive function was observed on the test of selective attention.

To evaluate the processes of Working Memory and inhibitory control in low and middle SES infants, Lipina et al. (2005) used a task of delayed-response paradigm. This study compared the performance of 280 Argentinian infants (six-to 14-months old) from Unsatisfied and Satisfied Basic Needs homes on the A-not B task. Results showed that children from low-SES background presented reduced measures of both accuracy and speed on measures of executive attention and alerting; indicating that poverty and its outcomes were responsible for modulating response conflict and inhibiting of distracting information.

To test the effect of low SES mothers being on medical assistance at the time of their children's birth, Farah et al. (2006) recruited thirty low SES African American children (17 girls) between the ages of 10 and 13 (mean age 11.7, SD= 1.0) and conducted research at Pennsylvania and Philadelphia Department of Recreation Summer Camps. The tasks applied were the Spatial working memory; the Two-back; the Go–No-Go task; and the Number Stroop. Results showed that the association between SES and neurocognitive development is highly significant and varies significantly in strength across the neurocognitive systems tested. Findings show that language and memory ability are closely related to SES disparities.

Evans and Schamberg (2009) set out to investigate the relationships between childhood poverty, chronic stress, and adult working memory. The authors hypothesized the following: (1) childhood poverty would interfere with WM in young adults; (2) the prospective relationship between childhood poverty and adult WM would be mediated by chronic stress exposure (i.e., poverty - chronic stress - WM). To investigate this, researchers measured chronic physiological stress by using allostatic load2_{- which is an index of cumulative} wear and tear on the body caused by repeated mobilizations of multiple physiological systems over time in response to environmental demands. Results showed that the greater the proportion of life growing up in poverty from

2_{Allostatic load is usually measured using a composite index of indicators of cumulative strain on several organs and}

tissues - primarily biomarkers (various measures that are sensitive to subtle changes in the biological state resulting from environmental exposure) associated with the neuroendocrine, cardiovascular, immune and metabolic systems

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birth to age 13 years, the shorter the span of sequential information 17-year-old adults could accurately hold in their working memory. On average adults raised in middle-income families could hold in WM a sequence of 9.44 items, whereas adults who grew up in poverty had a WM capacity of 8.50 items. Thus, the study suggests allostatic load during childhood significantly predicts WM in young adulthood. This reinforces the premise that SES is closely related to Executive Functions when it comes to WM capacity.

Within the field of cognitive flexibility, Clearfield and Niman (2012) conducted research on the effects of Socioeconomic Status (SES) on cognitive flexibility. This longitudinal study investigated the development of cognitive flexibility in low-income infants. Thirty-two infants (15 low-SES and 17 high-SES) were tested at 6, 9 and 12 months of age. To measure cognitive flexibility, the researchers administered a perseverative reaching task, where infants taught to reach to one location and then asked to switch to a second location. Findings showed that high-SES infants replicated the typical developmental trajectory, whereas the low-SES infants showed a delayed pattern.

Lipina et al. (2013) conducted a study with two hundred and fifty children (134 girls), aged M = 4.87, SD = 0.59 years, recruited from three school districts in the city of Buenos Aires, Argentina. Cognitive tasks were applied for three 40-minute sessions (two tasks per session). A socioeconomic scale (NES) assessing specific experience of poverty for children (i.e. health history, preschool attendance, books in the household, frequency of reading, computer and Internet use in the household) was administered (Spanish short-form of the Child Behavior Questionnaire (CBQ) as well as the Anxiety and Depression Hamilton scale. Children from UBN homes had lower efficacy on cognitive tasks related to the prefrontal/executive neurocognitive subsystem. Stroop3_{and ANT}4

3_{The Stroop Test consists of colors that are written in words but in the wrong color ink. The test-taker must be able to} state the color that the word is written in and be able to ignore whatever the actual word is. For example, if you see the word “red” but it’s written in blue ink, the correct answer would be “blue”. This test dates back to the 1930s and measures cognitive functioning.

4_{The ANT is a task designed to test three attentional networks: executive control, alerting, and orienting. The efficiency} of the executive network is examined by requiring the participant to respond by pressing two keys indicating the direction (left or right) of a central arrow surrounded by congruent, incongruent, or neutral flankers. Efficiency of the alerting network is assessed by changes in reaction time resulting from a warning signal. Efficiency of orienting is examined by changes in the reaction time that accompany cues indicating where the target will occur.

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showed no differences in reaction time when the two socioeconomic groups were compared. This contrasts previous findings which showed an impact of SES on ANT reaction time. The composite of Literacy activities was a mediator of SES effects on performance in tasks demanding fluid processing and spatial working memory. Thus, this was not true for attentional control, object working memory (i.e. Self-ordered) or planning.

Also interested in the relations between SES and EF skills, Leonard et al. (2015) recruited adolescents in Massachusetts from a variety of home and schooling environments (total of 58 participants; mean age: 14.42, range 13.08– 15.18; 27 males). Participants were divided into lower-SES and higher-SES groups based on whether they had received free or reduced-price lunch within 3 years before participation in the study. Cognitive tasks applied were: (1) Procedural Memory Task; (2) Working Memory Task and (3) A count span task. Participants underwent scanning and behavioral testing during the same visit. The behavioral tests were conducted outside of the scanner. Findings suggest that SES may have a selective influence on hippocampal-prefrontal-dependent working memory and little influence on striatal-dependent procedural memory. Lower-SES adolescents had worse working memory (reduced complex working memory span), but equivalent procedural memory (probabilistic classification learning) compared to the higher-SES adolescents. In other words, SES does not have a global influence on brain and behavior, but rather affects some structures and functions more than others.

More recently Finn et al. (2016) studied 7th and 8th graders attending public schools in urban and suburban middle schools. Research took place at the Massachusetts Institute of Technology. The tasks administered were the N-back and the Count Span task. Familial SES environment was operationalized by whether the children qualified for free or reduced lunch based on family income. Findings showed that behaviorally, the higher-income group had greater WM capacity and higher mathematics achievement scores.

Finally, research conducted by John et al. (2019) assessed children aged 4.5 - 5.5 years old. In this study, participants completed a Working Memory task involving a cognitive load component and a go/no go task in order to assess vigilance and inhibitory control. Results showed that children from low SES backgrounds presented lower accuracy scores for Working Memory skills, and

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inhibitory control; as well as a slower reaction time for Working Memory. Again, these findings show that the many underlying mechanisms encompassed by SES (poverty, stress, violence, and others already mentioned) present a strong relation with Executive Function skills.

The review of these empirical studies has shown that, all in all, outcomes suggest a link between SES, EFs, and scholastic achievement (reading and math outcomes). From the first one, conducted in the year 2011, up until the last study commented, conducted in 2019 – findings show the disparities between low vs high SES children when it comes to skills connected to: selective attention, executive attention, language, memory, and Working Memory capacity. We can conclude that Low-SES children present a delayed developmental trajectory when compared to higher-SES children and most importantly, studies show that SES and its underlying mechanisms do not have a global influence on the brain; but rather affect different structures in different ways. Results vary according to the tasks administered, the age-range, and the EF skills investigated.

Taking these issues into account, the present study intends to investigate the relations between SES and EFs in Brazilian students from Natal/RN – a population yet to be researched, and the effects that EF training might have on the scholastic outcomes of these children. We also seek to find out whether children from poor socioeconomic backgrounds (more vulnerable and disadvantaged children) might stand to gain the most from our gaming intervention than the students from privileged backgrounds.

2.3 TRAINING ON EXECUTIVE FUNCTIONS

In this section, we present the definition of Training, along with a review of the recent studies conducted in the field. We also discuss how Training might affect reading outcomes.

2.3.1 What is training?

Research has repeatedly confirmed Executive Functions as important prerequisites for the abilities to acquire knowledge and new skills. As mentioned

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in the previous sections, EFs are related to higher level cognitive abilities and play an important role in scholastic outcomes.

Emerging literature on EF demonstrates that there is a very strong interest in the malleability and trainability of EF skills in young children. Because of the protracted development of the brain circuitry associated with EFs – prefrontal cortex -, training becomes very promising and might hold substantial educational benefits (Zelazo et al., 2016; Thorell et al., 2009; Loosli et al., 2011; Carretti et al., 2014; Goldin et al., 2014; Segretin et al, 2014).

At this point it is important to pose the question: what is training? According to Pahor et al. (2108), brain training, also referred to as cognitive training, is defined as an intervention which is intended to improve the function of one or more basic cognitive processes. The training of the brain usually focuses on enhancing perception, motor control, memory and decision making.

The same authors assert that brain-training can either affect domain general and/or domain specific cognitive processes. Typically, the aim of brain training is domain general, since researchers aim for improvement in performances across a range of tasks, both trained and untrained, which rely upon the targeted cognitive domain.

As an example, if one could improve Working Memory (our ability to store and mentally manipulate multiple pieces of information), this could have a positive impact on many abilities such as: solving mathematical calculations, understanding complex ideas or making good decisions.

Thus, researchers in the field of Executive Function training have been aiming at not only improving aspects of EFs but seeking to obtain transfer to real-world manifestations (school performance, for example) as well. This is called the ‘holy grail’ of brain training, in other words, when training effects transfer far beyond its own context to benefit real-world cognition (Pahor et al. 2018).

Although brain training is considered an exciting field because of the many positive outcomes that might emerge from training the brain, the topic remains filled with controversy. In the literature, many research results are overstated, some studies fail to replicate and the extent of transfer from training to real world behaviors – such as academic abilities like reading, for example – is still heavily debated.

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Furthermore, although findings might seem encouraging, transfer effects are often small and often are not consistent across different studies.

As such, more questions are posed: to what extent is training limited to activities that strongly resemble the trained task? And does training truly transfer to untrained tasks? Although brain training often times has been somewhat regarded as sensationalist, emerging literature suggest that it is indeed possible to train basic cognitive processes (e.g. working memory) and obtain substantial changes in more complex cognitive tasks such as decision making, problem solving and visuospatial/mathematical skills.

As mentioned previously, EFs are a prime target for brain training since all real-world tasks heavily rely upon them. Nonetheless, EF training is a very difficult task because Executive Functions encompass a many process for which the neuronal mechanisms and underlying cognitive processes are not well understood (Pahor et al. 2018).

2.3.2 Empirical Studies on EF Training

In this section, we aim at presenting recent studies within the field of EF training. Thorell et al. (2009) administered computerized training in 48 preschool children (ages 4 and 5 years) for a period of 5 weeks (either visuo-spatial working memory or inhibition training). In this study, an active control group played commercially available computer games, and a passive control group took part in only pre- and post-testing. Children who trained on working memory showed significant improvement on the trained tasks; and they showed training effects on non-trained tests of spatial and verbal working memory, as well as transfer effects to attention. The group of children who trained on inhibition showed a significant improvement over time on two out of three trained task paradigms, but no significant improvements relative to the control groups on tasks measuring working memory or attention. In neither of the two interventions were there effects on non-trained inhibitory tasks. According to the authors, the results suggest that working memory training can have significant effects also among preschool children.

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Also interested in the relations between training and transfer effects of executive functions, Loosli et al. (2011) investigated whether a brief cognitive training intervention would result in a specific performance increase in the trained task, and whether there would be transfer effects to other non-trained measures. To do so, a computerized, adaptive working memory intervention was conducted with 9- to 11-year-old typically developing children (a total of 66 children). All of them attended the end of third grade or the beginning of fourth grade in elementary schools near Bern, Switzerland. A special variant of a WM task (used previously to train adults) was developed specifically for the study. In this version, participants had to identify the orientation of each picture in a series of animal pictures; that is, they had to decide whether an animal was presented correctly or upside-down. Immediately after presentation of the series, the children had to recall the order in which the animals were presented. Also, the training task was adaptive, forcing the participants to train at their WM capacity limit: After each successful trial, WM load was increased by one item, and after failure, it was reduced by one item. Measures for reading abilities were (1) pseudo words, (2) single words, and (3) text passages. Findings indicated that children significantly improved their performance in the trained task; and, compared to a matched control group, the experimental group significantly enhanced their reading performance after training.

Likewise, Carretti et al. (2014) examined whether reading comprehension in school children could be improved by comparing the efficacy of two different training programs. Both trainings involved metacognition and working memory, but one was based on listening comprehension while the other was based on reading comprehension. To do this, a sample of 159 students attending the fourth and fifth grades (ranging from 9-11 years) received training implemented by schoolteachers during 22 sessions (1 hours). Results suggest that comprehension can be indeed fostered by activities which focus specifically on metacognition and working memory.

Goldin et al. (2014) set out to investigate far transfer to language and math using a short software-based gaming intervention. They hypothesized the following: gaming intervention in school age children aimed at improving aspects of EF should transfer to real-world manifestations of school performance indexed by children’s grades. One hundred eleven low-SES

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typically developing children participated in the intervention over a period of 10 weeks. Children were divided into two groups. Participants in the experimental group played three adaptive computer games aimed at training working memory, planning, and inhibitory control skills; whereas participants in an active control group were trained on three equally motivating games that required similar motor responses, but which were less cognitive demanding. Children played at school only one game in each 15-min session, and a total of no more than three sessions per week. Before and after the intervention, school records of the children were obtained, and their EF performance was measured through several standardized tasks. The tasks administered were: (1) the child Attention Network Test; (2) the Heart-Flower Stroop - a nonverbal task that measures aspects of inhibitory control and and (3) Tower of London (TOL). Authors claim that the overall results from the cognitive batteries suggest that the training may, in effect, lead to an improvement of EF, but they also indicate that this increase is not expressed in all facets of EF or task contexts.

Also, within the field of EF training, Segretin et al. (2014) investigated cognitive enhancement and training. A total of 745 Argentinean children aged 3-5 years (2002 and 2004) were recruited to participate in the SIP - a longitudinal study implemented in three kindergartens (in the city of Buenos Aires. The program was an experimental, randomized, and controlled study and its main goal was to train cognitive performance in preschool children. Training sessions happened once a week (a total of 16 sessions), or twice a week (a total of 32 sessions) during 16 weeks in 1 year. Each session lasted for approximately 30-40 min each. To assess socioeconomic status, researchers applied a Socioeconomic Scale (NES) which considered numerous factors: parents’ education and occupation levels, overcrowding, housing and sanitation. In the year 2005, the same group of researchers recruited 382 Argentinean children aged 3-5 years. This study took place in Salta - Argentina and was called the CTP Program. Both programs used training activities to conduct the interventions. For the SIP, researchers administered the following: The Selective Attention task; The Corsi Blocks task used to assess visuospatial organization processes; The Tower of London task used to assess planning; The Flexible Item Selection Task; Stroop-like Day-Night task was administered to assess inhibitory control processes. Training activities for the CTP program