The Balance Between n-6 and n-3 and its Relation to Executive Function

C H A P T E R

4 The Balance Between n-6 and n-3 and its Relation to Executive Function Kelly W. Sheppard⁎,†, Carol L. Cheatham‡,§ ⁎

Nationwide Children’s Hospital, Center for Biobehavioral Health, Columbus, OH, United States †The Ohio State University, Department of Pediatrics, Columbus, OH, United States ‡University of North Carolina at Chapel Hill, Nutrition Research Institute, Kannapolis, NC, United States §University of North Carolina at Chapel Hill, Department of Psychology and Neuroscience, Chapel Hill, NC, United States

INTRODUCTION Fatty acids (FAs) are integral to every cell in the body. They are especially important in the brain where they fulfill structural and functional roles. The omega-6 (n-6) and omega-3 (n-3) FA are both important to neural tissues. Linoleic (LA; 18:2n-6) and linolenic (LNA; 18:3n-3) acids are essential; longer chain FA can be obtained from the diet or endogenously through a series of enzymatic steps. The latter method is thought to be relatively inefficient,1 but important factors such as genetics, epigenetics, and balance were not considered when that conclusion was drawn. Importantly, the balance between the n-6 and n-3 metabolic pathways is complex and not well understood. As detailed further, the n-6 and n-3 metabolic pathways compete for the elongases and desaturases necessary to produce the longer-chain FAs (see Fig. 1). These enzymes are under control of the FADS gene complex, and the delta-6 desaturase from the FADS2 gene is considered the rate-limiting enzyme. To predict the effects of an n-6 and n-3 imbalance, one must understand the genetics, the inherent differential affinities, and the various environmental influences, including diet; much research is needed to complete the understanding of this multifaceted system. In this chapter, we discuss research in which scientists utilized the n-6 to n-3 ratio. We provide the rationale for a change in terminology to “balance” rather than “ratio.” After providing an evolutionary perspective, we discuss in detail the relation between the n-6/n-3 balance and the development of higher cognitive abilities known collectively as executive functions (EFs).

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Omega-6 pathway

Omega-3 pathway

Diet

Diet

Linoleic acid (18:2n-6)

Alpha-linolenic acid (18:3n-3) Delta-6 Desaturase (FADS2)

Gamma-linolenic acid (18:3n-6)

Stearidonic acid (18:4n-3) Elongase (ELOVL5)

Dihomo-gamma-linolenic acid (20:3n-6)

Eicosatetraenoic acid (20:4n-3)

Delta-5 Desaturase (FADS1)

Arachidonic acid (20:4n-6) Elongase (ELOVL2)

Elongase (ELOVL5 or ELOVL2)

Adrenic acid (22:4n-6)

24:4n-6

Eicosapentaenoic acid (20:5n-3) Elongase (ELOVL2)

Docosapentaenoic acid (22:5n-3)

Delta-6 desaturase (FADS2)

24:5n-6

betaOx

24:5n-3

Delta-6 desaturase (FADS2)

Docosapentaenoic acid (23:5n-6)

Docosahexoenoic acid (22:6n-3)

betaOX

24:6n-3

FIG.  1  The metabolic pathways of n-3 and n-6 fatty acids. Adapted from Sheppard KW, Cheatham CL. Omega-6 to omega-3 fatty acid ratio and higher-order cognitive functions in 7- to 9-y-olds: a cross-sectional study. Am J Clin Nutr 2013;98(3):659–667.

EVOLUTIONARY PERSPECTIVE The human genome changes very slowly, and thus, humans today have the same or at least, a genome very similar to their Paleolithic ancestors. It has been suggested that we need to eat commensurate with our genes.2 How do we then know what the appropriate genomic diet would be? What was the ancestral diet? Distal theories are always laden with supposition, and thus, are only an approximation, at best, of reality. Although great care has gone into determining the diet of our Paleolithic ancestors,3–6 the fact is year-to-year climate and soil quality, in part, determine nutrient content of plant foods, and we cannot be certain what the weather and soil quality were thousands of years ago. Nonetheless, Eaton and his colleagues provide a well-researched and characterized estimate of micronutrient and energy intake in the ancestral diet.3,6 Given the nature of the hunter-gather life, we assume that gathered plant foods were eaten immediately with little processing or even cooking, which provides the best nutritive value from plants. Hunting was most likely only randomly successful, and thus, meat consumption was not a major source of energy. Anthropologists set the intake at 65:35 plant- to animal-based calories.7 Moreover, wild meat is generally quite lean. Thus, exogenous intake of the longer chain FA such as docosahexaenoic acid (DHA; 22:6n-3) was most likely negligible in non-coastal tribes.

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It is equally difficult to determine the ancestral FA intake ratio. Nonetheless, it has oft times been posited that the Paleolithic diet contained an n-6/n-3 ratio of 1:12,8,9 and as such, 1:1 is put forth as a gold standard goal for eating to match ones’ genes. The ratio purported to be found in the contemporary non-fish-eating Western diet is 20:1.9–11 However, it is important to note that researchers who have collected data on consumption in non-fish-eating populations in developed countries find an n-6/n-3 ratio of closer to 10:112–18 Adding to the complexity, it is now widely accepted that genes are not deterministic, but rather are switched on and off by epigenetics. This programming occurs, in part, in utero. With respect to nutrition, the fetus’ system is set based on maternal diet. The first evidence of this epigenetic programming of nutritional set points came from famine research: infants born to women who were pregnant during a famine have nutritional needs that have been adjusted to a world with few calories.19–23 Thus, whereas the genome may have not changed much since the Paleolithic Era, gene expression is individualized, and nutritional needs are based on familial experience rather than distal theories.

METABOLIC PATHWAYS Endogenous synthesis of the vital longer-chain FA arachidonic acid (AA; 20:4n-6) and DHA from their precursors LA and LNA, respectively, has two limiting factors: competition for enzymatic resources and genetically controlled production of those enzymes. Specifically, FA metabolism is limited by the delta-5 and delta-6 desaturase coded by the FADS genes.24–26 The polyunsaturated FAs (PUFAs) rely on delta-5 and delta-6 desaturase to synthesize the long-chain FAs (LC-PUFAs) AA and DHA from their precursors LA and LNA, respectively. As mentioned, LNA and LA are essential nutrients: they must be obtained from the diet. The n-3, n-6, and n-9 pathways compete for a limited supply of delta-5 and delta-6 desaturase coded for by the FADS genes and of elongases coded for by the ELOVL genes. Beyond the competition for resources, the supply of the delta-5 and delta-6 desaturase (and possibly the elongase) is further limited by an individual’s genotype. Single nucleotide polymorphisms (SNPs) in the FADS gene complex have been shown by others and us to be related to lower levels of FA in plasma 27,28 and in human milk.29–31 It follows that the need for exogenous DHA is dependent, in part, on an individual’s ability to synthesize endogenous long-chain FA from the essential parent FA: if an individual has the SNP, consumption of exogenous FA would be crucial. There is no consensus regarding the recommendations for the converse: if one does not have the SNP. Some researchers contend the endogenous conversion rate is so low, the DHA produced is inconsequential with the mean LNA:DHA rate ~0.047%,32,33 but results of studies have been, again, inconsistent34–36 and as mentioned, it is difficult to account empirically for all the potential influences on this complex system.

IMPORTANCE OF n-6/n-3 BALANCE One of the influences on this complex metabolic system is the balance between the n-6 and n-3 pathways. This balance has become known as the “ratio.” Use of this term by others and us has obfuscated, albeit unintentionally, other important data points. The ratio is merely a

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mathematical way to quantify the balance between the two pathways: it is a datapoint, not an ecologically relevant number. Indeed, given the complexity of the pathways and the many different intermediary FA, it is difficult to imagine that collapsing one’s data into a number that reflects total n-6 FA/total n-3 FA would allow one to draw valid conclusions, and its use may in fact obscure the actual predictors. Harris and colleagues detail this issue and provide an empirical example of the inclusion of n-6 in the variable of interest diminishing the actual and more salient finding that n-3 levels are related to risk of cardiovascular disease.37 That is, the ratio is a composite variable that should not be used on its own, but rather as part of an investigation of the individual FAs. In work detailed further, we have found that the relation of the ratio to cognitive data is further qualified by n-3 status.17,18 Thus, the ratio is a good statistical starting point if the focus remains on balance as the true predictor and if individual FAs are also assessed for their independent contributions to the outcome of interest. The balance between the two pathways (n-6 and n-3) has been empirically related to several disease states. As mentioned in the section Evolutionary Perspectives, it is thought that across time, the human diet has changed from an assumed nearly equal intake between the two pathways to a diet that is skewed to much higher n-6 intake (by as much as 10–20:1 n-6:n-3). Coincident with the change to higher n-6 intake is an increase in diseases of inflammation. All diseases have some degree of inflammation in their symptomology. Diseases specifically related to inflammation include allergies, some cancers, obesity, arthritis, and auto-immune disorders—all of which have been on the rise in Western countries. Metabolites of the n-6 pathway are pro-inflammatory; metabolites of the n-3 pathway are anti-inflammatory. Imbalance of dietary intake of these FA in favor of n-6 FAs, which would result in an increase in pro-inflammatory eicosanoids, has been implicated in atherosclerosis, obesity, diabetes, and autoimmune disorders38,39 Increasing dietary n-3, and thereby, improving the balance, has been shown to improve the symptomology of lupus40 and rheumatoid arthritis.41 Associations with psychological functions have also been shown. For example, the relation between the balance and depressive mood states42 and other psychological diseases such as the early stages of Alzheimer’s43 have been established. Interestingly and beyond dietary intake, the balance of FAs stored in adipose tissue is related to cognitive function: lower n-6 to n-3 content of tissue is related to better cognitive function.44 These are only a few examples of the importance of an n-6 to n-3 balance in the prevention of disease states. It is difficult to determine what the proper balance should be in any one individual. Individual differences exist as a function of fetal programming, dietary intake, genetics, epigenetics, and even, mitochondrial function. As mentioned previously, some clues are available from the research done on the ancestral diet. There are also potential indications of the optimal balance that can be gleaned from the system itself. The genes that code for the desaturases involved in the metabolism of FA are regulated by dietary LC-PUFAs such as AA and DHA. The FADS genes that code for the desaturases delta-5 and delta-6 are upregulated when the diet does not contain enough PUFA. Importantly, those same genes are downregulated when the balance between the pathways equalizes.45 From this animal work, we can extrapolate to humans a homeostatic predisposition for a one-to-one balance of the n-6 and n-3 FAs. Therefore, those consuming the typical American diet or even, the diets in most developed non-coastal societies (1, 10–20) are at a much higher risk for disease based on diet alone. Necessarily, the research regarding the interactions between the n-6 and n-3 pathways have been carried out for, the most part, animal studies. It is becoming clear that this ­system

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is very complex and that there are several genes, differential affinities, and individual differences involved. Work with humans is ongoing. Because the brain areas that contain the highest levels of n-3 FAs subserve the cognitive abilities memory and EFs (hippocampus and frontal areas, including prefrontal cortex), associations among the FAs and these cognitive functions are studied most often. Importantly, longitudinal supplementation studies that have not found effects of the supplementation early on have found effects when the EF abilities begin to develop at preschool age46 attesting to the specificity of the effects of FAs on cognitive development.47 In what follows, we begin with the definition of EFs, their developmental trajectories, and the neural substrates that support them. We then detail the research that has been completed exploring the balance between the FA pathways and the human ability to perform higher order cognitive functions such as working memory, planning, and inhibitory control.

EXECUTIVE FUNCTIONS EFs are higher-order cognitive processes that control behavior, emotion, and cognition48–51 and are subserved by the frontal lobes.52 EFs develop from early childhood into adulthood,53,54 and are linked to theory of mind (understanding that others may have a differing viewpoint from one’s own)55–57 and math and reading abilities.49,58 EFs develop over a long time-span, with research starting as early as 2 years of age and extending well into adulthood.53,59,60 They are important functions for daily life in adulthood, and as such, it is important to understand what nutritional support is necessary for optimal development and function.

Definition of EF The definition of EF has been approached from brain-based research and behavior-based research. The central role of the frontal cortex in EF has been emphasized in brain-based research for several decades,52,61,62 but recent work has expanded to studying EF as subserved by networks, all of which include frontal areas, but also incorporate areas such as the amygdala, hippocampus, and cerebellum depending on the EF of interest.61,63–66 Behaviorfocused research has often defined EFs as control of goal-directed behaviors51,67,68 or regulatory processes that control automatic responses.50,56,69,70 In these investigations, EF are usually divided into discrete functions, such as inhibitory control, working memory, planning, set-shifting, updating, and attentional control. Attempts have been made to bridge these two research approaches for a cohesive definition of EF that incorporates both brain and behavioral aspects and acknowledges the complexity of EF, which develop across a long-time span.53,59,60 These attempts are important for understanding the role of nutrients (such as n-3 and n-6 FA) in EF. First, the role of complex neural networks in EF requires understanding the different developmental trajectories of the brain areas involved and how nutrients are taken up and used in those brain areas. Second, the distinct EFs studied have unique elements, but their similarities (e.g., in cognitive flexibility) are important for a unified definition and for understanding the role of specific nutrients. Third, the overarching concept of control or regulation that is seen in most approaches to EF is important for understanding how EF are measured, and therefore, what might be affected by changes in nutrient availability.

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Neural Substrates Subserving EFs The frontal cortex consists of Brodmann areas 4, 6, 8–11, and 44–47. It is structurally defined as the area in front of the central sulcus and above the lateral sulcus (Sylvian fissure). The frontal cortex is large and complex, and its structural and functional organization are still being studied today.71 It is generally divided into three main areas when studied: a lateral section, a medial section, and an orbital section. These areas have direct connections to other brain areas, which provide clues as to their roles in various cognitive functions. There are two functional gradients that are important when studying EF: the medial-lateral gradient and the dorsal-ventral gradient. The connectivity of each area of the frontal cortex helps us understand why various nutritional deficiencies or supplements may affect some functions and not others, and helps us understand where we need to focus efforts if attempting to support development or prevent decline. Fig. 2 shows the general connections and flow of information in the neural substrates that support EF.

Medial-Lateral Gradient Medial areas of the frontal cortex (including the medial prefrontal cortex) are typically found to be involved in action monitoring,72 and connect to areas such as the anterior cingulate cortex (ACC), which is related to error monitoring and correction; the amygdala, which is connected to processing threats and fear-inducing stimuli; and the temporal lobe, including the hippocampus,73 which is a clearinghouse of sorts for memory information. Action monitoring and error correction are important elements of daily life that are under the purview of EF.74 Lateral frontal areas tend to be involved in broader cognitive control, with significant Parietal lobe including sensory integration areas

Temporal lobe including hippocamp us, amygdala, and basal ganglia

Dorsal Medial: Action monitoring Connect to anterior cingulate cortex (error monitoring), hippocampus (memory), and amygdala (fear and emotion)

Dorsal prefrontal cortex Occipital lobe including visual cortex

Lateral: Broad cognitive control Connections within prefrontal cortex Connections to parietal areas

Ventral prefrontal cortex Ventral Cerebellum

Caudal/posterior

Rostral/anterior

Dorsal PFC Internally driven control of behavior Connections to temporal areas (hippocampus, amygdala, and basal ganglia) Connections to parietal areas (sensory integration)

Ventral PFC Emotionally laden control of behavior Inhibition and shifting and motor responses Connections to occipital areas (visual) Connections to cerebellum (motor) Left lateral

Medial

Right lateral

FIG. 2  Diagram of information flow in the brain for executive functions. Sagittal view of brain from Clipart Library 2016.

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connections to other prefrontal areas and the parietal cortex.71 These connections support findings that lateral frontal areas underlie working memory and perception.75

Dorsal-Ventral Gradient The dorsal-ventral gradient in the frontal cortex is less well-understood and studied than the medial-lateral gradient, but ventral areas of the frontal cortex are thought to be more involved in emotionally laden information processing (sometimes called “hot” EF). These ventral areas connect to visual cortices, occipital areas, and fusiform areas.71 More ventral areas have been connected to language abilities76 and to inhibition and shifting performance,77 which are important EF. Dorsal areas of the frontal cortex have been heavily linked to working memory and updating,77 and specifically dorsolateral areas have been linked to internally driven control of behavior.71,78

Functional Connections It is important to highlight two additional brain areas functionally connected to the frontal cortex that are important for EF. The hippocampus, a brain area in the temporal lobe linked to spatial processing and memory, is physically connected to frontal areas through the dentate gyrus and fornix. Functionally, the hippocampus has been found to be involved in working memory and inhibition tasks through its connections to areas involved in the medial-lateral and dorsal-ventral gradients.79–81 It holds a seat of importance that has not been fully elucidated, but the hippocampus is involved in mature use of EF. In addition, the cerebellum, the brain area responsible for executing motor movements, is functionally connected to the frontal cortex and thus, is implicated in EF. In both laboratory EF tasks and daily life, EF often require motor movements, such as responding according to task rules (e.g., pressing a button) or executing a planned action (e.g., walking through a store picking up groceries). Evolutionarily newer areas of the cerebellum have also been linked to complex motor sequences that require coordination by an executive.66 The cerebellum and prefrontal cortex develop along similar trajectories (physical and temporal) 61,82 and become increasingly connected as we age.82 The cerebellum also connects to the frontal cortex across the medial-lateral and dorsal-ventral gradients, implying its high level of importance to all EF.83

Development These functionally distinct gradients in the frontal cortex have led to some consistent conclusions regarding the role of the frontal cortex in EF, such as the role of the dorsolateral prefrontal cortex (DLPFC) in working memory and the ventromedial prefrontal cortex (VMPFC) and orbitofrontal prefrontal cortex (OPFC) in inhibitory control.84 It is important to note that these frontal areas (and the functions they subserve) have a protracted development period. The prefrontal cortex is the last area of the brain to mature, and performance on EF tasks continues to improve well into adulthood.84 The functional connectivity and segregation of function mentioned briefly earlier, therefore, develops slowly. Two main changes characterize the development of a mature frontal cortex and related EF: a change from diffuse to focal activity and increased segregation and integration of brain areas.

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Diffuse to Focal Activity Studies of functional brain development have often found that early, immature brain activity when completing a task is more diffuse than later, mature brain activity, especially with EF.65,85–89 The development of EF involves increasingly distinct pathways of activation that depend on task demands90 such that immature EF (i.e., failure or inadequate performance often seen in younger children) activate frontal regions generally, and mature EF (i.e., reliably successful performance often seen in adults) activate distinct neural networks.87,89 There is evidence that the increase in focal activity is related to attenuation of activation in areas no longer required for task performance.85 This increase in focal activity is seen across domains, including mentalizing, attentional control, motor control, and emotion regulation.89

Integration and Segregation of Function Linked to the movement from diffuse to focal activity across development is increased in segregation and integration of function.83,91 As EF develops, specific brain areas are used for specific functions, as in examples offered earlier. However, there is also increased integration among brain areas, such that the frontal cortex connects to more areas in the brain (e.g., the cerebellum), allowing the formation of more complex networks to support more complex functions. This segregation and integration mirrors the overall developmental ­trajectory in the brain, which includes pruning of gray matter (segregation, more efficient use of specific brain areas for specific tasks) and increases in white matter tracts (­integration, myelinated axons used for long-distance communication between brain areas).92–99 Increased segregation and integration are generally linked to improved behavioral performance on EF tasks.83,89 Researchers also find that EF task performance clusters on a single factor in early childhood, but can be dissociated into three or more factors from later childhood onward.50,100,101 In models of EFs in adults, an executive component is seen as the seat of control of other functions 102,103 that produces a coherent response through representing rules and rule structures,70,104 inhibiting distracting or incorrect information,105,106 updating information while completing a task,87 and finally, providing a correct response or series of responses to the situation. These distinct functions are fairly easily dissociated, and the most commonly studied EFs include working memory, inhibitory control, set shifting, and planning. The picture of EF in children is less clear. In some models, EFs are considered to consist of three distinct functions in children67,100 generally comprising working memory, inhibitory control, and set shifting, whereas other models have still found EF to be a single factor in young children.50 Developmentally, EFs are seen as becoming increasingly differentiated both in terms of behavioral function and cortical activation. Fig. 3 illustrates the inter-dependencies and complexities of EF. Research on EF development has focused on where children differ from adults—what errors they make in tasks that require an executive. As Smith et al.107 explain, errors on EF tasks in childhood can be seen as problems with action, problems with inhibition, or problems with working memory. For instance, children and infants can correctly indicate where an object belongs in a sorting task through words or eye gaze.108,109 and only fail at search tasks when

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FIG. 3  Diagram of executive functions and their relations.

asked to execute that search.107,110–112 In the brain, the prefrontal cortex and cerebellum are developing connections throughout the first 2 years of life, and those connections are thought to support knowledge of the correct sorting or reaching behavior to guide actual actions.61 There is an inherent development of the connectivity between distant brain areas and an implied differentiation of function that allows specificity in the use of rules and actions to correctly respond to task demands.113 The executive is the organizer of information from brain areas required for control of behavior, emotion, and cognition, and the increases in coordination and efficiency required to develop mature EF are going to be constrained by the brain’s structural and functional development. Neuronal structure and function are directly related to the availability of nutrients needed to produce neurons, neurotransmitters, and receptors. Broad changes across development include increases in gray matter until age 4 when it begins to decline and increases in white matter steadily into adulthood.97,98,114,115 Later, changes in gray matter development differ between brain areas. Peaks in gray matter occur around adolescence and differ between the frontal, parietal, temporal, and occipital lobes.116 The changes in white and gray matter are related to changes in the composition of the lipid bilayer and increased myelination that changes the overall balance of cholesterol, proteins, and fats in the brain.99 When studying FA, it is important to understand how the brain is developing during a given period and what the optimal balance of FA may be to support structure and function.117

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BALANCE OF FAS AND EFS n-3 FA have been the main focus of investigations into FA, and yet n-6 FAs, as described earlier, are not only also prevalent in the brain, they also play integral and complementary roles to n-3 FA.118–121 Consumption of FA should support the brain’s need for both n-6 and n-3 FAs. Moreover, an imbalance of these two families of FA may prevent the beneficial effects of supplementation. EFs in particular are more susceptible to imbalances in n-6 and n-3 FA consumption because of the large networks involved in EF and their extended developmental trajectory. For instance, Innis and de la Presa Owens122 found that supplementing rats with fish oil (high in n-3 FA) was negatively correlated with dopamine and serotonin levels in the rat brain. Dopamine and serotonin are two highly prevalent monoamine neurotransmitters in the frontal cortex, and alterations in these monoamines have been shown to affect EF.123–125 Interestingly, serotonin levels were highest in the brains of rats in high n-6 group, followed by the brains of rats in the high n-3, and the lowest serotonin levels were found in the brains of rats in the medium n-6 group. The groups who consumed the two unbalanced ratios (371.5 and 0.12) had the highest levels of serotonin despite one being very high in n-6 and one being very high in n-3. These findings indicate that the balance of FA plays an important role in the ultimate outcome in the brain, and simply the amounts of n-6 or n-3 cannot be the sole focus of research. Additionally, the clear role for FA in neuronal growth, a process that would be particularly important during periods of considerable brain growth like the first 2 years of life and the adolescent years, implies that the balance of n-6 and n-3 FA will be important for cognitive functions that develop during those periods and functions that require large brain networks such as EFs.

Inhibitory Control Inhibitory control is defined as the ability to “suppress inappropriate but prepotent responses of various kinds.”56 It represents the ability to take the large amounts of information we get on a daily basis and select the relevant pieces for use while inhibiting irrelevant or distracting information. Research has indicated that inhibitory control undergoes considerable development in early childhood, with particularly rapid improvement from 2 to 5 years old.57,126,127 Inhibitory control tasks reliably activate the frontal cortex, and the development of inhibitory control is related to changes in the use of neural resources as the complexity of the inhibitory control requirements increases. Children will become proficient at simpler inhibitory control tasks before more complex tasks. Brain activation clearly distinguishes between children who have developed the ability to control inhibition and those who have not. For instance, adults had greater ACC activation across inhibitory control tasks (area of the brain involved in attentional control), but they only had different DLPFC activation during the more complex inhibitory control tasks compared to adolescents.128 Supporting connections between the ACC and DLPFC are important for supporting EF development. Similarly, mature inhibitory control not only means knowing the correct response but carrying out the correct action in accordance with the correct response. Inhibitory control requires efficient coordination of a frontal network and connections to cerebellar areas for motor responses.61 Rule-switching, a complex form of inhibitory control, in adults involves coordination of the ventrolateral prefrontal cortex (VLPFC) and the pre-supplementary motor areas

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(pre-SMA). Children reach adult levels of activation of the pre-SMA by adolescence, but even adolescents show different activation of the VLPFC compared to adults.104 Understanding the nutrient needs of each of the brains areas involved in EF is essential to supporting their optimal development. The frontostriatal network frequently discussed with inhibitory control is generally considered to include the PFC, ACC, striatum, and cerebellar areas (see Fig. 2). All of these areas are affected by n-3 FA deficiency and changes in the balance of n-6 and n-3 FA.129–131 However, each brain area tends to respond differently. In the face of n-3 deficiency, the frontal cortex tends to become depleted of n-3 FA, and levels of n-6 FA only increase somewhat, whereas the striatum and cerebellum tend to accumulate more n-6 FA and not lose as much DHA.132,133 The best accretion of ARA and DHA in the frontal cortex and cerebellum occurs in ratios close to 4:1 and not diets focused on one or the other FA family.130,131 These alterations in the FA composition of membranes affects dopamine receptor density in the frontal cortex129 and serotonin receptor density in the frontal cortex and ACC,134 which affects communication within the frontostriatal network as monoamine neurotransmitters are highly prevalent in these brain areas. Disruption to dopamine and serotonin receptors has been shown to disrupt EF task performance in animals.123,124 The full picture of neurotransmitter function that supports EF is, of course, complex, but these monoamines have been consistently implicated125 such that the role of FA in monoamine receptors and neurotransmission is likely an important element of their role in EF.

Working Memory Working memory is defined as a system for temporarily holding information and using it for complex cognitive tasks.102 Baddeley and Hitch’s widely accepted tri-partite model of adult working memory135 is composed of the central executive and two subsystems. The central executive and subsystems of the tri-partite model of working memory develop at different rates and in different ways. The central executive coordinates the activity of the two subsystems, the phonological loop and visuospatial sketchpad, which are directly responsible for the information being stored and processed. Similar to inhibitory control, mature working memory cannot be achieved until the frontal areas are connected to response elements (visual, motor, or verbal). Investigations into the development of working memory highlight increases in the roles of distinct brain areas and increased connectivity between frontal, parietal, temporal, and occipital areas. Success on working memory tasks across development involves increasing specificity in the brain areas involved. Successful infants had greater electroencephalography (EEG) coherence across the whole brain in a simple working memory task, whereas children 4.5 years old who were successful had increased coherence only between the medial frontal and posterior temporal areas and the medial frontal and occipital areas.65 EEG coherence is thought to be indicative of the connections between brain areas, and greater coherence likely indicates more connectivity and organization between brain areas.136 In general, improvements in speed and accuracy of working memory proceed linearly across childhood and adolescence.53,137,138 However, investigations that use a variety of tasks often find that patterns of performance begin to diverge. Performance on phonological and visuospatial tasks was highly correlated among 4- and 5-year olds, but those correlations

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decreased over time until there were clearly distinct domains with phonological working memory tasks correlated with one another and distinct from visuospatial working memory tasks.138 Across middle childhood and adolescence, there are increases in activity in frontal, parietal, and temporal areas that correspond to increases in accuracy and speed of processing.139–141 There is also evidence of a lateralization across development that is related to improved performance87 and reflects the type of stimulus being held in memory and manipulated (spatial vs object number).142 The development of working memory involves a process of differentiation (behaviorally and in use of cortical resources) and increased involvement of the frontal cortex. Evidence points to the important role of n-6 and n-3 FA. First, the hippocampus, a brain area recruited during memory and spatial processing tasks, is another area of the brain that accumulates considerable n-3 and n-6 FA.143 The hippocampus is also sensitive to deficiency and imbalance of FA.130,131 Working memory tasks, particularly spatial tasks, recruit both the frontal cortex and hippocampus. This recruitment of two brain areas sensitive to alterations in FA balance makes working memory a function of specific interest in understanding the role of FA. Alterations in monoamine vesicles in the presynaptic terminal,144 neuron size and amount of dendritic branching,145 and basal acetylcholine activity and muscarinic receptor density146 have been found in the hippocampus in response to n-3 deficiency. All these alterations relate to the ability of the hippocampus to communicate with other brain areas. However, adding DHA at levels similar to other studies did not replete n-3 FA levels in the brain or improve working memory performance in previously deficient rats. Instead, increasing the level of DHA and lowering n-6 FA to lower the ratio repleted brain levels of n-3 FA and improved performance.147 The working memory literature also highlights the role of differentiation in the development of mature EF. Over time, brain function becomes more distinct in response to specific stimuli and specific processing requirements, and with aging, brain structure and function reduce in differentiation. This process of integration and differentiation through the growth of neurons, synapses, and dendritic branching combined with synaptic pruning supports the development of necessary connections and decreases unused or excess connections. Typically, researchers have demonstrated that n-3 FA increase neuronal growth and dendritic branching, and n-6 FA decrease neuronal growth and dendritic branching in both the hippocampus and frontal cortex.145,148,149 A balance between n-6 and n-3 FA could therefore support a system that is changing neuronal connections and structure in support of newly developing functions. It would be expected that balanced FA pathways would support the process of integration and differentiation associated with mature working memory.

Planning Planning is an EF characterized by assessing a goal, determining how to reach the goal, executing the steps, and then evaluating errors and goal attainment.150,151 Planning recruits similar cortical resources to working memory and inhibitory control. The dorsolateral and rostrolateral PFC,152 inferior frontal gyrus153 and superior frontal areas154 are found to be activated during planning tasks. Planning develops well into the adult years, and even studies with adults demonstrate considerable variability in performance.59,155 For instance, when investigating EF in children 3–12 years old and a group of adults, researchers found that

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c­ hildren reached adult performance on the simpler problems by age 6 but did not reach adult performance until age 12 on the more difficult problems.156 The contribution of n-6 and n-3 FA to planning is similar to the role of FA in the ­development of inhibitory control and working memory, which set the groundwork for the development of planning. The appropriate balance of FA during the development of inhibitory control and working memory will likely set the stage for optimal planning development. The balance between n-6 and n-3 FA predicts planning task performance, particularly number of moves and time required to solve complex problems.17,18 Additionally, there is evidence that the optimal balance that supports planning changes across development. In one study, younger children (7–9 years old) performed best with balanced n-6 and n-3 FA levels measured in blood and through dietary intake, but older children (10–12 years old) were best supported by higher n-3 FA, and less balance between n-3 and n-6 FA.17 The findings were mirrored by the balance (or imbalance) of n-3 and n-6 FA that supported brain activity during optimal performance of the planning tasks. Across these ages, children improve in their inhibitory control,105,128 working memory,53,137 and planning155,156 abilities. However, these changes reflect both a movement toward adultlevel performance and brain activation and distinct differences.88,105 Some of these differences are related to pubertal changes in hormones and concomitant changes in brain structure and function. n-3 FA have been found to increase neurite outgrowth and dendritic branching145,157 that is important during periods of brain growth. High n-6 intake may inhibit the metabolism and use of n-3 FA that are important to brain growth. Younger children, whose brains are not undergoing the rapid growth associated with puberty, may require a balanced diet because both n-6 and n-3 FA are important for neuronal communication.129,158,159 Conversely, puberty brings with it changes in brain structure and function that could be best supported with a balance of n-6 and n-3 FA that provide more n-3 FA. n-3 FA support neurite growth in the frontal cortex and hippocampus,122,157 and DHA has been found to affect monoamine neurotransmission during puberty in rats.160 Monoamine neurotransmission has been shown to be affected by hormones161,162 and n-6 and n-3 FA.129,144,163 These developmental considerations make FA intake recommendations more difficult, but also highlight the importance of considering the balance of n-6 and n-3 FA and being precise in examining when to supplement.

CONCLUSION The balance of n-6 and n-3 FAs is likely particularly important to the frontal cortex because of the unique demands of EF. The need to coordinate between many brain areas and to coordinate both incoming information and outgoing information to produce a coherent response would likely be susceptible to imbalances in FA because of the integral nature of both n-6 and n-3 FA to neuronal growth and communication. The frontal cortex is usually the focus of neuroimaging investigations of EF, but EFs are actually subserved by additional functional cortical networks that incorporate areas outside the frontal cortex. There are different networks related to different elements of EF, such as trial-by-trial updating and sustained maintenance of overall goal-directed behaviors in adults 78, and those networks undergo a process of segregation (decreases in short-range connections) and integration (increases in

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long-range connections) across development.83 Therefore, whereas the needs of the frontal cortex are important, understanding the FA requirements of different structures within the EF networks and how those structures communicate is necessary. It is useful to approach EF in terms of the role of the frontal cortex52,156 and from the lens of the inherent qualities of the functions that fall under the umbrella term “EFs.”70,109

References 1. Brenna JT, Salem N, Sinclair AJ, Cunnane SC. α-Linolenic acid supplementation and conversion to n-3 longchain polyunsaturated fatty acids in humans. Prostaglandins Leukot Essent Fatty Acids. 2009;80(2–3):85–91. 2. Simopoulos AP. The importance of the ratio of omega-6/omega-3 essential fatty acids. Biomed Pharmacother. 2002;56(8):365–379. 3. Eaton SB, Eaton III SB, Konner MJ. Paleolithic nutrition revisited: a twelve-year retrospective on its nature and implications. Eur J Clin Nutr. 1997;51:207–216. 4. Eaton SB, Konner M. Paleolithic nutrition: a consideration of its nature and current implications. N Engl J Med. 1985;312(5):283–289. 5. Eaton SB, Eaton III SB, Konner MJ. An evolutionary perspective enhances understanding human nutritional requirements. J Nutrition. 1996;126:1732–1740. 6. Eaton SB, Eaton IIISB, Sinclair AJ, Cordain L, Mann NJ. Dietary intake of long-chain polyunsaturated fatty acids during the paleolithic. In: Simopoulos A, ed. World Review of Nutrition & Dietetics. Basel, Switzerland: Karger; 1998:12–23. Vol. 83. 7. Lee RB. What hunters do for a living, or, how to make out on scarce resources. In: Lee RB, DeVore I, eds. Man the Hunter. Chicago: Aldine; 1968:30–48. 8. Simopoulos  AP. Evolutionary aspects of diet, the omega-6/omega-3 ratio and genetic variation: Nutritional implications for chronic diseases. Biomed Pharmacother. 2006;60(9):502–507. 9. Simopoulos  AP. Evolutionary aspects of diet: the omega-6/omega-3 ratio and the brain. Mol Neurobiol. 2011;44(2):203–215. 10. Innis SM. Omega-3 fatty acid biochemistry: perspectives from human nutrition. Mil Med. 2014;179(11):82–87. 11. Elmadfa I, Kornsteiner M. Fats and fatty acid requirements for adults. Ann Nutr Metab. 2009;55(1–3):56–75. 12. Fleith M, Clandinin MT. Dietary PUFA for preterm and term infants: review of clinical studies. Crit Rev Food Sci Nutr. 2005;45(3):205–229. 13. Friesen RW, Innis SM. Dietary arachidonic acid to EPA and DHA balance is increased among Canadian pregnant women with low fish intake. J Nutr. 2009;139(12):2344–2350. 14. Ervin RB, Wright JD, Wang CY, Kennedy-Stephenson J. Dietary intake of fats and fatty acids for the United States population: 1999–2000. Adv Data. 2004;(348):1–6. 15. Keim SA, Branum AM. Dietary intake of polyunsaturated fatty acids and fish among US children 12–60 months of age. Matern Child Nutr. 2015;11(4):987–998. 16. Sheppard  KW, Cheatham  CL. Omega-6/omega-3 fatty acid intake of children and older adults in the U.S.: Dietary intake in comparison to current dietary recommendations and the healthy eating index. Lipids Health Dis. 2018;17(1):43. 17. Sheppard KW, Cheatham CL. Executive functions and the omega-6-to-omega-3 fatty acid ratio: a cross-­sectional study. Am J Clin Nutr. 2017;105(1):32–41. 18. Sheppard KW, Cheatham CL. Omega-6 to omega-3 fatty acid ratio and higher-order cognitive functions in 7- to 9-y-olds: a cross-sectional study. Am J Clin Nutr. 2013;98(3):659–667. 19. Ravelli AC, van der Meulen JH, Michels RP, et al. Glucose tolerance in adults after prenatal exposure to famine. Lancet. 1998;351(9097):173–177. 20. Ravelli  GP, Stein  ZA, Susser  MW. Obesity in young men after famine exposure in utero and early infancy. N Engl J Med. 1976;295(7):349–353. 21. Roseboom TJ, Painter RC, van Abeelen AF, Veenendaal MV, de Rooij SR. Hungry in the womb: What are the consequences? Lessons from the Dutch famine. Maturitas. 2011;70(2):141–145. 22. Susser M, Stein Z. Timing in prenatal nutrition: a reprise of the Dutch famine study. Nutr Rev. 1994;52(3):84–94. 23. Tobi EW, Lumey LH, Talens RP, et al. DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific. Hum Mol Genet. 2009;18(21):4046–4053.

A.  OMEGA FATTY ACIDS AND BRAIN: AN OVERVIEW

REFERENCES 57

24. Rzehak  P, Heinrich  J, Klopp  N, et  al. Evidence for an association between genetic variants of the fatty acid desaturase 1 fatty acid desaturase 2 (FADS1 FADS2) gene cluster and the fatty acid composition of erythrocyte membranes. Br J Nutr. 2009;101(1):20–26. 25. Schaeffer L, Gohlke H, Muller M, et al. Common genetic variants of the FADS1 FADS2 gene cluster and their reconstructed haplotypes are associated with the fatty acid composition in phospholipids. Hum Mol Genet. 2006;15(11):1745–1756. 26. Nwankwo  JO, Spector  AA, Domann  FE. A nucleotide insertion in the transcriptional regulatory region of FADS2 gives rise to human fatty acid delta-6-desaturase deficiency. J Lipid Res. 2003;44(12):2311–2319. 27. Steer  CD, Hibbeln  JR, Golding  J, Davey Smith  G. Polyunsaturated fatty acid levels in blood during pregnancy, at birth and at 7 years: Their associations with two common FADS2 polymorphisms. Hum Mol Genet. 2012;21(7):1504–1512. 28. Lupu  DS, Cheatham  CL, Corbin  KD, Niculescu  MD. Genetic and epigenetic transgenerational implications related to omega-3 fatty acids. Part I: Maternal FADS2 genotype and DNA methylation correlate with polyunsaturated fatty acid status in toddlers: an exploratory analysis. Nutr Res. 2015;35(11):939–947. 29. Xie L, Innis SM. Genetic variants of the FADS1 FADS2 gene cluster are associated with altered (n-6) and (n-3) essential fatty acids in plasma and erythrocyte phospholipids in women during pregnancy and in breast milk during lactation. J Nutr. 2008;138(11):2222–2228. 30. Molto-Puigmarti C, Plat J, Mensink RP, et al. FADS1 FADS2 gene variants modify the association between fish intake and the docosahexaenoic acid proportions in human milk. Am J Clin Nutr. 2010;91(5):1368–1376. 31. Cheatham CL, Sheppard KW. Synergistic effects of human milk nutrients in the support of infant recognition memory: an observational study. Nutrients. 2015;7(11):9079–9095. 32. Pawlosky RJ, Hibbeln JR, Novotny JA, Salem Jr N. Physiological compartmental analysis of alpha-linolenic acid metabolism in adult humans. J Lipid Res. 2001;42(8):1257–1265. 33. Lin  YH, Llanos  A, Mena  P, Uauy  R, Salem Jr N, Pawlosky  RJ. Compartmental analyses of (2)H(5)-alphalinolenic acid and (13)C-U-eicosapentaenoic acid toward synthesis of plasma labeled 22:6-23 in newborn term infants. Am J Clin Nutrit. 2010;92(2):284–293. 34. Li D, Sinclair A, Wilson A, et al. Effect of dietary alpha-linolenic acid on thrombotic risk factors in vegetarian men. Am J Clin Nutrit. 1999;69(5):872–882. 35. Fokkema MR, Brouwer DA, Hasperhoven MB, Martini IA, Muskiet FA. Short-term supplementation of lowdose gamma-linolenic acid (GLA), alpha-linolenic acid (ALA), or GLA plus ALA does not augment LCP omega 3 status of Dutch vegans to an appreciable extent. Prostaglandins Leukot Essent Fatty Acids. 2000;63(5):287–292. 36. Ezaki O, Takahashi M, Shigematsu T, et al. Long-term effects of dietary alpha-linolenic acid from perilla oil on serum fatty acids composition and on the risk factors of coronary heart disease in Japanese elderly subjects. J Nutr Sci Vitaminol (Tokyo). 1999;45(6):759–772. 37. Harris WS, Assaad B, Poston WC. Tissue omega-6/omega-3 fatty acid ratio and risk for coronary artery disease. Am J Cardiol. 2006;98(4A):19i–26i. 38. Simopoulos AP. An increase in the omega-6/omega-3 fatty acid ratio increases the risk for obesity. Nutrients. 2016;8(3):128. 39. Simopoulos AP. The importance of the omega-6/omega-3 fatty acid ratio in cardiovascular disease and other chronic diseases. Exp Biol Med (Maywood). 2008;233(6):674–688. 40. Borges MC, Santos Fde M, Telles RW, Correia MI, Lanna CC. Polyunsaturated omega-3 fatty acids and systemic lupus erythematosus: What do we know? Rev Bras Reumatol. 2014;54(6):459–466. 41. Calder  PC. Fatty acids and inflammation: the cutting edge between food and pharma. Eur J Pharmacol. 2011;668(Suppl 1):S50–S58. 42. Ryback  R. Bioelectrical modulators and the cell membrane in psychiatric medicine. Psychopharmacol Bull. 2001;35(4):5–44. 43. Freund-Levi  Y, Eriksdotter-Jonhagen  M, Cederholm  T, et  al. Omega-3 fatty acid treatment in 174 patients with mild to moderate Alzheimer disease: OmegAD study: a randomized double-blind trial. Arch Neurol. 2006;63(10):1402–1408. 44. Stilling F, Wolk A, Religa D, et al. Adipose tissue fatty acid composition and cognitive impairment. Nutrition. 2018;54:153–157. 45. Wijendran V, Downs I, Srigley CT, et al. Dietary arachidonic acid and docosahexaenoic acid regulate liver fatty acid desaturase (FADS) alternative transcript expression in suckling piglets. Prostaglandins Leukot Essent Fatty Acids. 2013;89(5):345–350.

A.  OMEGA FATTY ACIDS AND BRAIN: AN OVERVIEW

58

4.  THE BALANCE BETWEEN n-6 AND n-3 AND ITS RELATION TO EXECUTIVE FUNCTION

46 Helland IB, Smith L, Saarem K, et al. Maternal supplementation with very-long-chain n-3 fatty acids during pregnancy and lactation augments children’s IQ at 4 years of age. Pediatrics 2003;111(1):e39–44. 47. Cheatham CL. Omega-3 fatty acids and the development of cognitive abilities: a review of DHA supplementation studies. CAB Rev Perspect Agric Vet Sci Nutr Nat Res. 2008;3(1):1–15. 48. Carlson SM. Developmentally sensitive measures of executive function in preschool children. Dev Neuropsychol. 2005;28:595–616. 49. Bull R, Espy KA, Wiebe SA. Short-term memory, working memory, and executive functioning in preschoolers: longitudinal predictors of mathematical achievement at age 7 years. Dev Neuropsychol. 2008;33(3):205–228. 50. Wiebe  SA, Sheffield  T, Nelson  JM, Clark  CA, Chevalier  N, Espy  KA. The structure of executive function in 3-year-olds. J Exp Child Psychol. 2011;108(3):436–452. 51. Zelazo PD, Carter A, Reznick JS, Frye D. Early development of executive function: a problem-solving framework. Rev Gen Psychol. 1997;1:198–226. 52. Roberts  RJ, Pennington  BF. An interactive framework for examining prefrontal cognitive processes. Dev Neuropsychol. 1996;12(1):105–126. 53. Conklin HM, Luciana M, Hooper CJ, Yarger RS. Working memory performance in typically developing children and adolescents: behavioral evidence of protracted frontal lobe development. Dev Neuropsychol. 2007;37:103–128. 54. Pelphrey KA, Reznick JS. Working memory in infancy. Adv Child Dev Behav. 2003;31:173–227. 55. Carlson SM, Moses LJ. Individual differences in inhibitory control and children’s theory of mind. Child Dev. 2003;72:1032–1053. 56. Carlson SM, Moses LJ, Breton C. How specific is the relation between executive function and theory of mind? Contributions of inhibitory control and working memory. Infant Child Develop. 2002;11(2):73–92. 57. Carlson  SM, Moses  LJ, Claxton  LJ. Individual differences in executive functioning and theory of mind: An investigation of inhibitory control and planning ability. J Exp Child Psychol. 2004;87(4):299–319. 58. Bull R, Espy KA, Senn TE. A comparison of performance on the towers of London and Hanoi in young children. J Child Psychol Psychiatry. 2004;45:743–754. 59. Luciana M, Nelson CA. The functional emergence of prefrontally-guided working memory systems in four- to eight-year-old children. Neuropsychologia. 1998;36:273–293. 60. Wiebe SA, Morton JB, Buss AT, Spencer JP. The emergence of executive function. Monogr Soc Res Child Dev. 2014;79(2):1–132. 61. Diamond A. Close interrelation of motor development and cognitive development and of the cerebellum and prefrontal cortex. Child Dev. 2000;71:44–56. 62. Chandler DJ, Waterhouse BD, Gao WJ. New perspectives on catecholaminergic regulation of executive circuits: evidence for independent modulation of prefrontal functions by midbrain dopaminergic and noradrenergic neurons. Front Neural Circuits. 2014;8:53. 63. Logue  SF, Gould  TJ. The neural and genetic basis of executive function: attention, cognitive flexibility, and response inhibition. Pharmacol Biochem Behav. 2014;123:45–54. 64. Rohr CS, Dreyer FR, Aderka IM, et al. Individual differences in common factors of emotional traits and executive functions predict functional connectivity of the amygdala. Neuroimage. 2015;120:154–163. 65. Bell MA, Wolfe CD. Changes in brain functioning from infancy to early childhood: evidence from EEG power and coherence during working memory tasks. Dev Neuropsychol. 2007;31:21–38. 66. Riva D, Cazzaniga F, Esposito S, Bulgheroni S. Executive functions and cerebellar development in children. Appl Neuropsychol Child. 2013;2(2):97–103. 67. Garon N, Bryson SE, Smith IM. Executive function in preschoolers: a review using an integrative framework. Psychol Bull. 2008;134(1):31–60. 68. Carlson SE, Werkman SH, Rhodes PG, Tolley EA. Visual-acuity development in healthy preterm infants: effect of marine-oil supplementation. Am J Clin Nutr. 1993;58(1):35–42. 69. Miyake A, Friedman NP. The nature and organization of individual differences in executive functions: four general conclusions. Curr Dir Psychol Sci. 2012;21(1):8–14. 70. Zelazo PD, Frye D. Cognitive complexity and control: II. The development of executive function in childhood. Curr Direct Psychol Sci. 1998;7(4):121–128. 71. Orr JM, Smolker HR, Banich MT. Organization of the human frontal pole revealed by large-scale DTI-based connectivity: implications for control of behavior. PLoS One. 2015;10(5):e0124797. 72. Bonini F, Burke B, Liegeois-Chauvel C, Regis J, Chauvel P, Vidal F. Action monitoring and medial frontal cortex: leading role of supplementary motor area. Science. 2014;343:888–891.

A.  OMEGA FATTY ACIDS AND BRAIN: AN OVERVIEW

REFERENCES 59

73. Gilbert SJ, Gonen-Yaacovi G, Benoit RG, Volle E, Burgess PW. Distinct functional connectivity associated with lateral versus medial rostral prefrontal cortex: a meta-analysis. Neuroimage. 2010;53(4):1359–1367. 74. de la Vega A, Chang LJ, Banich MT, Wager TD, Yarkoni T. Large-scale meta-analysis of human medial frontal cortex reveals tripartite functional organization. J Neurosci. 2016;36(24):6553–6562. 75. Bludau S, Eickhoff SB, Mohlberg H, et al. Cytoarchitecture, probability maps and functions of the human frontal pole. Neuroimage. 2014;93(Pt 2):260–275. 76. Neubert FX, Mars RB, Thomas AG, Sallet J, Rushworth MF. Comparison of human ventral frontal cortex areas for cognitive control and language with areas in monkey frontal cortex. Neuron. 2014;81(3):700–713. 77. Collette F, Hogge M, Salmon E, Van der Linden M. Exploration of the neural substrates of executive functioning by functional neuroimaging. Neuroscience. 2006;139(1):209–221. 78. Dosenbach  NU, Fair  DA, Miezin  FM, et  al. Distinct brain networks for adaptive and stable task control in ­humans. Proc Natl Acad Sci U S A. 2007;104(26):11073–11078. 79. Toepper M, Markowitsch HJ, Gebhardt H, et al. Hippocampal involvement in working memory encoding of changing locations: an fMRI study. Brain Res. 2010;1354:91–99. 80. Wu  JQ, Peters  GJ, Rittner  P, Cleland  TA, Smith  DM. The hippocampus, medial prefrontal cortex, and selective memory retrieval: evidence from a rodent model of the retrieval-induced forgetting effect. Hippocampus. 2014;24(9):1070–1080. 81. Mala H, Andersen LG, Christensen RF, et al. Prefrontal cortex and hippocampus in behavioural flexibility and posttraumatic functional recovery: reversal learning and set-shifting in rats. Brain Res Bull. 2015;116:34–44. 82. Ramnani N. The primate cortico-cerebellar system: anatomy and function. Nat Rev Neurosci. 2006;7(7):511–522. 83. Fair DA, Dosenbach NU, Church JA, et al. Development of distinct control networks through segregation and integration. Proc Natl Acad Sci U S A. 2007;104(33):13507–13512. 84. Casey  BJ, Giedd  J, Thomas  KM. Structural and functional brain development and its relation to cognitive ­development. Biol Psychol. 2000;54:241–257. 85. Durston S, Davidson M, Tottenham N, et al. A shift from diffuse to focal cortical activity with development. Dev Sci. 2006;9(1):1–20. 86. Moriguchi Y, Hiraki K. Prefrontal cortex and executive function in young children: a review of NIRS studies. Front Hum Neurosci. 2013;7:867. 87. Tsujii T, Yamamoto E, Masuda S, Watanabe S. Longitudinal study of spatial working memory development in young children. Neuroreport. 2009;20(8):759–763. 88. Tsujimoto  S. The prefrontal cortex: functional neural development during early childhood. Neuroscientist. 2008;14(4):345–358. 89. Kelly AM, Di Martino A, Uddin LQ, et al. Development of anterior cingulate functional connectivity from late childhood to early adulthood. Cereb Cortex. 2009;19(3):640–657. 90. Buss AT, Fox N, Boas DA, Spencer JP. Probing the early development of visual working memory capacity with functional near-infrared spectroscopy. Neuroimage. 2014;85(Pt 1):314–325. 91. Hwang  K, Velanova  K, Luna  B. Strengthening of top-down frontal cognitive control networks underlying the development of inhibitory control: a functional magnetic resonance imaging effective connectivity study. J Neurosci. 2010;30(46):15535–15545. 92. Barnea-Goraly N, Menon V, Eckert M, et al. White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. Cereb Cortex. 2005;15(12):1848–1854. 93. Lenroot  RK, Giedd  JN. Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci Biobehav Rev. 2006;30(6):718–729. 94. Stevens MC, Skudlarski P, Pearlson GD, Calhoun VD. Age-related cognitive gains are mediated by the effects of white matter development on brain network integration. Neuroimage. 2009;48(4):738–746. 95. Giedd JN, Blumenthal J, Jeffries NO, et al. Brain development during childhood and adolescence: a longitudinal MRI study. Nat Neurosci. 1999;2:861–863. 96. Pfefferbaum A, Mathalon DH, Sullivan EV, Rawles JM, Zipursky RB, Lim KO. A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood. Arch Neurol. 1994;51:874–887. 97. Toga AW, Thompson PM, Sowell ER. Mapping brain maturation. Trends Neurosci. 2006;29(3):148–159. 98. Sowell  ER, Trauner  DA, Gamst  A, Jernigan  TL. Development of cortical and subcortical brain structures in childhood and adolescence: a structural MRI study. Develop Med Child Neurol. 2002;44:4–16. 99. Barkovich AJ, Kjos BO, Jackson DE, Norman D. Normal maturation of the neonatal and infant brain: MR imaging at 1.5 T. Neuroradiology. 1988;166:173–180.

A.  OMEGA FATTY ACIDS AND BRAIN: AN OVERVIEW

60

4.  THE BALANCE BETWEEN n-6 AND n-3 AND ITS RELATION TO EXECUTIVE FUNCTION

100. Miyake A, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD. The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: a latent variable analysis. Cogn Psychol. 2000;41(1):49–100. 101. Hughes C, Ensor R, Wilson A, Graham A. Tracking executive function across the transition to school: a latent variable approach. Dev Neuropsychol. 2010;35(1):20–36. 102. Baddeley A. Working memory. Science. 1992;255:556–559. 103. Baddeley A. Exploring the central executive. Q J Exp Psychol. 1996;49A:5–28. 104. Crone  EA, Donohue  SE, Honomichl  R, Wendelken  C, Bunge  SA. Brain regions mediating flexible rule use during development. J Neurosci. 2006;26(43):11239–11247. 105. Schroeter ML, Zysset S, Wahl M, von Cramon DY. Prefrontal activation due to Stroop interference increases during development—an event-related fNIRS study. Neuroimage. 2004;23(4):1317–1325. 106. Casey BJ, Richards JE. A refractory period for the heart rate response in infant visual attention. Dev Psychobiol. 1991;24(5):327–340. 107. Smith LB, Thelen E, Titzer R, McLin D. Knowing in the context of acting: The task dynamics of the A-not-B error. Psychol Rev. 1999;106:235–260. 108. Zelazo PD, Reznick JS, Pinon DE. Response control and the execution of verbal rules. Dev Psychol. 1995;31:508–517. 109. Zelazo PD. The development of conscious control in childhood. Trends Cogn Sci. 2004;8(1):12–17. 110. Cathro DM, Forsyth CC, Cameron J. Adrenocortical response to stress in newborn infants. Arch Dis Childhood. 1969;44:88–95. 111. Diamond A. Development of the ability to use recall to guide action, as indicated by infants’ performance on AB. Child Dev. 1985;56:868–883. 112. Diamond A, Doar B. The performance of human infants on a measure of frontal cortex function, the delayed response task. Dev Psychobiol. 1989;22:271–294. 113. Morton JB, Munakata Y. Active versus latent representations: a neural network model of perseveration, dissociation, and declage. Dev Psychobiol. 2002;40:255–265. 114. Carlson SE, Goldfarb S. A sensitive enzymatic method for determination of free and esterified tissue cholesterol. Clin Chim Acta. 1977;79(3):575–582. 115 Carskadon MA, Dement WC. Normal sleep and its variations. In M.H. Kryger, T. Roth, & W.C. Dement (Eds.), Principles and Practice of Sleep Medicine, 5th ed., (pp 16-26). St Louis: Elsevier Saunders. 116. Carlson  SE, Werkman  SH, Montalto  MB, Tolley  EA. Visual acuity development of preterm (PT) infants fed docosahexaenoic acid (DHA) and arachidonic acid (ARA): effect of age at supplementation. Pediatr Res. 1999;45:279A. 117. Wainwright PE. Dietary essential fatty acids and brain function: a developmental perspective on mechanisms. Proc Nutr Soc. 2007;61(01):61–69. 118. Carlson SE. Docosahexaenoic acid and arachidonic acid in infant development. Semin Neonatol. 2001;6(5):437–449. 119. Carlson SE, Werkman SH, Peeples JM, Cooke RJ, Tolley EA. Arachidonic acid status correlates with first year growth in preterm infants. Proc Natl Acad Sci U S A. 1993;90:1073–1077. 120. Connor  S, Tenorio  G, Clandinin  MT, Sauve  Y. DHA supplementation enhances high-frequency, stimulation-­ induced synaptic transmission in mouse hippocampus. Appl Physiol Nutr Metab. 2012;37(5):880–887. 121. Richards DA, Bliss TVP, Richards CD. Differential modulation of NMDA-induced calcium transients by arachidonic acid and nitric oxide in cultured hippocampal neurons. Eur J Neurosci. 2003;17(11):2323–2328. 122. Innis SM, De La Presa Owens S. Dietary fatty acid composition in pregnancy alters neurite membrane fatty acids and dopamine in newborn rat brain. J Nutr. 2001;131:118–122. 123. Puig MV, Miller EK. Neural substrates of dopamine D2 receptor modulated executive functions in the monkey prefrontal cortex. Cereb Cortex. 2015;25(9):2980–2987. 124. Maiti P, Gregg LC, McDonald MP. MPTP-induced executive dysfunction is associated with altered prefrontal serotonergic function. Behav Brain Res. 2016;298(Pt B):192–201. 125. Robbins TW, Roberts AC. Differential regulation of fronto-executive function by the monoamines and acetylcholine. Cereb Cortex. 2007;17(Suppl 1):i151–i160. 126. Diamond A, Kirkham NZ, Amso D. Conditions under which young children can hold two rules in mind and inhibit a prepotent response. Dev Psychol. 2002;38:352–362. 127. Zelazo PD, Reznick JS. Age-related asynchrony of knowledge and action. Child Dev. 1991;62:719–735. 128. Rubia K, Smith AB, Woolley J, et al. Progressive increase of frontostriatal brain activation from childhood to adulthood during event-related tasks of cognitive control. Hum Brain Mapp. 2006;27(12):973–993.

A.  OMEGA FATTY ACIDS AND BRAIN: AN OVERVIEW

REFERENCES 61

129. Delion S, Chalon S, Herault J, Guilloteau D, Besnard J-C, Durand G. Chronic dietary alpha-linolenic acid deficiency alters dopaminergic and serotoninergic neurotransmission in rats. J Nutr. 1994;124:2466–2476. 130. Jumpsen J, Lien EL, Goh YK, Clandinin MT. During neuronal and glial cell development diet n-6 to n-3 fatty acid ratio alters the fatty acid composition of phosphatidylinositol and phosphatidylserine. Biochim Biophys Acta. 1997;1347:40–50. 131. Jumpsen J, Lien EL, Goh YK, Clandinin MT. Small changes of dietary (n-6) and (n-3)/fatty acid content ratio alter phosphatidylethanolamine and phosphatidylcholine fatty acid composition during development of neuronal and glial cells in rats. J Nutr. 1997;127:724–731. 132. Carlson SE, Salem Jr. N. Essentiality of omega 3 fatty acids in growth and development of infants. World Rev Nutr Diet. 1991;66:74–86. 133. Levant B, Ozias MK, Carlson SE. Specific brain regions of female rats are differentially depleted of docosahexaenoic acid by reproductive activity and an (n-3) fatty acid-deficient diet. J Nutr. 2007;137:130–134. 134. du Bois  TM, Deng  C, Bell  W, Huang  XF. Fatty acids differentially affect serotonin receptor and transporter binding in the rat brain. Neuroscience. 2006;139(4):1397–1403. 135. Gathercole SE. The development of memory. J Child Psychol Psychiatry. 1998;39:3–27. 136. Thatcher RW, Krause PJ, Hrybyk M. Cortico-cortical associations and EEG coherence: a two-compartmental model. Electroencephalogr Clin Neurophysiol. 1986;64:123–143. 137. Luciana M, Conklin HM, Hooper CJ, Yarger RS. The development of nonverbal working memory and executive control processes in adolescents. Child Dev. 2005;76:697–712. 138. Gathercole SE, Pickering SJ, Ambridge B, Wearing H. The structure of working memory from 4 to 15 years of age. Dev Psychol. 2004;40(2):177–190. 139. Blain-Briere B, Bouchard C, Bigras N, Cadoret G. Development of active control within working memory: active retrieval versus monitoring in children. Int J Behav Dev. 2013;38(3):239–246. 140. Klingberg  T, Forssberg  H, Westerberg  H. Increased brain activity in frontal and parietal cortex underlies the development of visuospatial working memory capacity during childhood. J Cogn Neurosci. 2002;14:1–10. 141. Nelson CA, Monk CS, Lin J, Carver LJ, Thomas KM, Truwit CL. Functional neuroanatomy of spatial working memory in children. Dev Psychol. 2000;36:109–116. 142. Smith EE, Jonides J, Koeppe RA, Awh E, Schumacher EH, Minoshima S. Spatial versus object working memory: PET investigations. J Cogn Neurosci. 1995;7:337–356. 143. Martinez  M. Tissue levels of polyunsaturated fatty acids during early human development. J Pediatr. 1992;120:S129–S138. 144. Zimmer L, Delpal S, Guilloteau D, Aioun J, Durand G, Chalon S. Chronic n-3 polyunsaturated fatty acid deficiency alters dopamine vesicle density in the rat frontal cortex. Neurosci Lett. 2000;284:25–28. 145. Ahmad A, Murthy M, Moriguchi T, Salem N, Greiner RS. A decrease in cell size accompanies a loss of docosahexaenoate in the rat hippocampus. Nutr Neurosci. 2002;5(2):103–113. 146. Aid S, Vancassel S, Poumes-Ballihaut C, Chalon S, Guesnet P, Lavialle M. Effect of a diet-induced n-3 PUFA depletion on cholinergic parameters in the rat hippocampus. J Lipid Res. 2003;44(8):1545–1551. 147. Ikemoto  A, Ohishi  M, Sato  Y, et  al. Reversibility of n-3 fatty acid deficiency-induced alterations of learning behavior in the rat: level of n-6 fatty acids as another critical factor. J Lipid Res. 2001;42:1655–1663. 148. Ahmad A, Momenan R, van Gelderen P, Moriguchi T, Greiner RS, Salem Jr. N. Gray and white matter brain volume in aged rats raised on n-3 fatty acid deficient diets. Nutr Neurosci. 2004;7(1):13–20. 149. Ikemoto  A, Kobayashi  T, Watanabe  S, Okuyama  H. Membrane fatty acid modifications of PC12 cells by arachidonate or docosahexaenoate affect neurite outgrowth but not norepinephrine release. Neurochem Res. 1997;22:671–678. 150. Lezak MD. The problem of assessing executive functions. Int J Psychol. 1982;17:281–297. 151. Welsh MC, Pennington BF. Assessing frontal lobe functioning in children: views from developmental psychology. Dev Neuropsychol. 1988;4(3):199–230. 152. Baker  SC, Rogers  RD, Owen  AM, et  al. Neural systems engaged by planning: a PET study of the tower of London task. Neuropsychologia. 1996;34:513–526. 153. Fincham JM, Carter S, van Veen V, Stenger VA, Anderson JR. Neural mechanisms of planning: a computational analysis using event-related fMRI. Proc Natl Acad Sci U S A. 2002;99(5):3346–3351. 154. Morris RG, Ahmed S, Syed GM, Toone BK. Neural correlates of planning ability: frontal lobe activation during the tower of London test. Neuropsychologia. 1993;31(12):1367–1378.

A.  OMEGA FATTY ACIDS AND BRAIN: AN OVERVIEW

62

4.  THE BALANCE BETWEEN n-6 AND n-3 AND ITS RELATION TO EXECUTIVE FUNCTION

155. Luciana M, Collins PF, Olson EA, Schissel AM. Tower of London performance in healthy adolescents: the development of planning skills and associations with self-reported inattention and impulsivity. Dev Neuropsychol. 2009;34(4):461–475. 156. Welsh MC, Pennington BF, Groisser DB. A normative-developmental study of executive function: a window on prefrontal function in children. Dev Neuropsychol. 1991;7(2):131–149. 157. Calderon F, Kim HY. Docosahexaenoic acid promotes neurite growth in hippocampal neurons. J Neurochem. 2004;90(4):979–988. 158. Fang YJ, Zhou MH, Gao XF, Gu H, Mei YA. Arachidonic acid modulates Na+ currents by non-metabolic and metabolic pathways in rat cerebellar granule cells. Biochem J. 2011;438(1):203–215. 159. Kim SJ, Zhang Z, Saha A, et al. Omega-3 and omega-6 fatty acids suppress ER- and oxidative stress in cultured neurons and neuronal progenitor cells from mice lacking PPT1. Neurosci Lett. 2010;479(3):292–296. 160. Weiser MJ, Wynalda K, Salem Jr. N, Butt CM. Dietary DHA during development affects depression-like behaviors and biomarkers that emerge after puberty in adolescent rats. J Lipid Res. 2015;56(1):151–166. 161. Rubinow DR, Schmidt PJ, Roca CA. Estrogen-serotonin interactions: implications for affective regulation. Biol Psychiatry. 1998;44:839–850. 162. Epperson CN, Wisner KL, Yamamoto BY. Gonadal steroids in the treatment of mood disorders. Psychosom Med. 1999;61:676–697. 163. Zimmer L, Vancassel S, Cantagrel S, et al. The dopamine mesocorticolimbic pathway in affected by deficiency in n-3 polyunsaturated fatty acids. Am J Clin Nutr. 2002;75:662–667.

A.  OMEGA FATTY ACIDS AND BRAIN: AN OVERVIEW