Is there a link between brain's energy consumption and human experience?

Is there a link between brain's energy consumption and human experience?

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I was read the article (in Scientific American Mind) about energy consumption of brain. There are:

Say you are learning a new skill-how to juggle or speak Spanish. Neuroscientists have made the fascinating observation that when we do something completely novel, a broad range of brain areas becomes active. As we become more skilled at the task, however, our brain becomes more focused: we require only the essential brain regions and need increasingly less energy to perform that task. Once we have mastered a skill-we become fluent in Spanish-only the brain areas directly involved remain active. Thus, learning a new skill requires more brainpower than a well-practiced activity.

Overall, though, on an individual level, our brain adapts and becomes more efficient as we gain mastery. We build new connections among neurons to keep pace with the greater demand on our neural resources. As our skill level grows in a particular area, our brain will inevitably require less energy to perform that task.

I tried to check what was written there. I tried to find experienced facts that refute or support this article. I did not find anything.

Question: are there experimental scientific data that show a decrease in energy consumption by the brain, while doing a certain activity, as professionalism grows? Or maybe there are experimental data that show the opposite? Or is there really no correlation between energy consumption and the growth of professionalism?

How Many Calories Can the Brain Burn by Thinking?

Here's how much energy you can burn when you put your mind to the test.

In 1984, the World Chess Championship was called off abruptly, due to the worryingly emaciated frame of Anatoly Karpov, an elite Russian player who was competing for the title. Over the preceding five months and dozens of matches, Karpov had lost 22 lbs. (10 kilograms), and competition organizers feared for his health.

Karpov's wasn't alone in experiencing the extreme physical effects of the game. While no chess competitor has experienced such profound weight loss since then, elite players can reportedly burn up to an estimated 6,000 calories in one day — all without moving from their seats, ESPN reported.

Is the brain responsible for this massive uptake of energy? And does that mean that thinking harder is a simple route to losing weight? To delve into that question, we first need to understand how much energy is used up by a regular, non-chess-obsessed brain.

When the body is at rest — not engaged in any activity besides the basics of breathing, digesting and keeping itself warm — we know that the brain uses up a startling 20% to 25% of the body's overall energy, mainly in the form of glucose.

That translates to 350 or 450 calories per day for the average woman or man, respectively. During childhood, the brain is even more ravenous. "In the average 5- to 6-year-old, the brain can use upwards of 60% of the body's energy," said Doug Boyer, an associate professor of evolutionary anthropology from Duke University. Boyer researches anatomical and physiological changes associated with primate origins.

This glucose-guzzling habit actually makes the brain the most energy-expensive organ in the body, and yet it makes up only 2% of the body's weight, overall.


In today’s fast-paced lives people need vigor to keep up with their demanding schedules and lifestyles. Often, they need some assistance in doing so. Caffeine is a naturally occurring chemical and is referred to as an 𠇊ncient wonder drug” (McCarthy et al., 2008) for its potential to revive weary workaholics. It was discovered in the coffee bean (Coffea arabica) in Arabia, the tea leaf (Thea sinensis) in China, the kola nut (Cola nitida) in West Africa, and the cocoa bean (Theobroma cacao) in Mexico (Chou, 1992). Caffeine products are so widely distributed these days that abuse of the substance may be unnoticed. In fact, caffeine is the world’s most widely consumed stimulant, with 54% of adults in America consuming on average three cups of coffee a day (Chen and Parrish, 2008). Aside from occurring organically in tea and coffee, caffeine is now an additive in soft drinks, energy drinks, chocolates, bottled water, chewing gum, and medication (Mednick et al., 2008). The aim of this paper is to elicit an awareness of the neurophysiological effects of caffeine. This article emphasizes caffeine’s potential effects on the nervous system within the context of increased caffeinated energy drink consumption around the world.

Climate Interpreter

Humans transfer and transform energy from the environment into forms useful for human endeavors. Currently, the primary sources of energy used by humans include fuels, like coal, oil, natural gas, uranium, and biomass. All these fuels—except biomass—are nonrenewable. Primary sources of energy also include renewables, such as sunlight, wind, moving water, and geothermal energy.

Fossil fuels contain energy captured millions of years ago from sunlight by living organisms. The energy in fossil fuels such as oil, natural gas, and coal comes from energy that producers (plants and algae) captured from sunlight long ago. Energy stored in these fuels is released by burning them, which also releases carbon dioxide into the atmosphere.

Human demand for energy is increasing.

For resources in addition to those featured below, follow these links:

Humans harness energy from any available resource and the demand for that energy is ever increasing.

Be efficient and economical with your energy use. This leaves more energy for all—including you—in the future.


George F. Cahill, Jr., then an associate professor of Medicine at Harvard Medical School and director of the Joslin Research Laboratory, was one of a very few clinical investigators who thought that the metabolism of starving humans should be reinvestigated in detail. In 1965, I was afforded a fellowship position in metabolism under the tutelage of Dr. Cahill, who in conjunction with his other academic appointments served on the professional staff of the Peter Bent Brigham Hospital. He was a creative and colorful medical director who had assembled a vibrant, cohesive research laboratory that was staffed by outstanding junior faculty, fellows, and proud, hard working, bright technicians who strove for exactness. The Peter Bent Brigham Hospital had a National Institutes of Health-supported clinical research center where patients could be housed and continuously observed during experimental protocols. A classical study by Cahill and colleagues was published in 1966 in The Journal of Clinical Investigation [ 4 ], which reported the hormone-fuel interrelationships during a 1-week fast (subjects consumed only water, salt, and vitamins during their starvation period) in six healthy subjects and two patients with type 2 diabetes mellitus. This article laid some of the groundwork for subsequent studies of prolonged starvation in obese humans.

When we began studying the energy requirements of adult humans and determining the organ or regional metabolism in these individuals, there were considerable gaps in our knowledge. It was probable that 1 g of urinary nitrogen could be equated to hepatic synthesis of about 3 g of glucose, that glucose synthesis occurred primarily from protein but not from fat, and that the brain used about 125 g of glucose daily to meet its energy requirements. In addition, the quantity of glucose stored as glycogen in the body was limited to approximately 1 day's supply. It was also known that only one-half of the body nitrogen (protein mass) could be mobilized during starvation, before death occurred. An average adult has about 1,000–1,200 g of nitrogen (mainly as muscle protein), but only 500–600 g can be mobilized before death occurs. This suggests that only 1,500–1,800 (500–600 × 3) g of glucose could be synthesized in the body during that period. If the brain continued to oxidize 100–145 g of glucose daily during starvation, survival would be limited to a minimum of 10 (1,500/145) and to a maximum of 18 (1,800/100) days. These calculations did not match the facts known at that time. First, obese humans consuming only water could usually live about 2 months. Second, to synthesize 100–145 g of glucose daily, the urinary excretion rate of nitrogen would have to be about 33 (100/3) to 48 (145/3) g the quantities of urinary nitrogen that were excreted during starvation were much less than these estimates.

We recognized the discrepancy between the requirement of the brain for glucose and the quantity of nitrogen excreted during starvation [ 2 ]. However, the quantity of nitrogen and the complete nature of the nitrogenous compounds excreted in the urine had not been clearly defined at that time. Furthermore, there was a verbal controversy regarding the ratio of urinary nitrogen and glucose production, and the sites of glucose production in the body during starvation had not been definitively established. Nonetheless, the quantity of glucose that can be totally oxidized to CO2 and water is considerably less than the 100–145 g/day required by the nervous system. Therefore, some fuel other than glucose must be providing the energy for the brain during starvation. When we began studying metabolic adaptations during starvation in humans, we did not know how long a person could fast and what fuels would be used by specific tissues. Once new insight began to accumulate, the energy requirements of all organs and the body as a whole had to be reevaluated.

5 Health Problems Linked to Energy Drinks

Concerns over the potentially harmful effects of energy drinks, especially when they’re combined with alcohol, have been growing in recent years.

A story in the New York Times today (Nov. 15) added to that concern, noting that the Food and Drug Administration (FDA) has received reports of 13 deaths linked to 5-Hour Energy, an energy drink. The drinks contain about 215 milligrams of caffeine, the equivalent of about two cups of coffee.

Here, a rundown of five worrisome health issues that have been linked to downing stimulating drinks:

Heart problems

In recent years, the company that markets 5-Hour Energy has filed about 30 reports with the FDA of serious injuries associated with its products, including heart attacks, according to the New York Times story.

And in 2007, a 28-year-old Australian man suffered cardiac arrest after consuming eight cans of an energy drink, containing 80 mg of caffeine each, over seven hours. The patient did not have a history of chest pain.

Caffeine and other compounds in energy drinks can boost heart rate and blood pressure, said Dr. John Higgins, associate professor of medicine at the University of Texas Medical School in Houston.

Caffeine can cause heart cells to release calcium, which may affect heartbeat, leading to arrhythmia, Higgins said. The drinks may also disrupt the normal balance of salts in the body, which has been linked to arrhythmia as well.

However, there is not enough evidence to say unequivocally that energy drinks cause heart problems. More research is needed to determine the amount of energy drinks people need to consume in order to experience these negative effects, Higgins said.

The risk of miscarriage

The FDA has also received one report linking a miscarriage to consumption of 5-Hour Energy.

Studies examining the effects of caffeine on miscarriage have been mixed. A 2006 study of more than 1,000 pregnant women found that those who consumed more than 200 mg of caffeine per day (from coffee, tea, soda or hot chocolate) were about twice as likely to have a miscarriage compared with pregnant women who did not drink caffeine. However, a study published in 2008 found no link between caffeine consumption (regardless of the amount) and the risk of miscarriage at 20 weeks of pregnancy.

Because study findings have not been conclusive, the American College of Obstetricians and Gynecologists advises that pregnant women limit caffeine consumption to 200 mg per day.

An increased risk of alcohol injury and dependence

Studies suggest that combining alcohol and energy drinks can be dangerous.

Although caffeine is a stimulant, research suggests it does not "counteract" the sedating effects of alcohol. There is concern that mixing alcohol and energy drinks may keep people awake for a longer period of time, allowing them to consume more alcohol than they ordinarily would, according to an editorial published last year in the Journal of the American Medical Association.

A 2011 study of about 1,100 college students found those who downed energy drinks frequently were about 2.5 times more likely to meet the diagnostic criteria for alcohol dependence than those who did not consume energy drinks. The link may be due to the practice of mixing alcohol and energy drinks, or drinking caffeine to recover from a hangover, according to the JAMA editorial. It could also be that caffeine's effects on the brain play a role in addiction, the editorial says.

Risk of drug abuse

Another study of 1,060 students found that energy drink consumption in the second year of college was associated with an increased risk of prescription drug abuse (use of stimulants or prescription painkillers without a prescription) in the third year of college.

One explanation for the link "is that energy drinks, like prescription drugs … might be regarded by some students as safer, more normative, or more socially acceptable than using illicit 'street' drugs," the researchers wrote in a 2010 issue of the Journal of Addiction Medicine.

Impaired cognition

Although some students rely on energy drinks to pull all-nighters to study for exams, there’s some evidence that the excessive levels of caffeine in the drinks impair cognition. A small 2010 study found that drinking moderate amounts of caffeine, about 40 mg, improved performance on a test of reaction time, but drinking higher amounts &mdash equivalent to the levels found in a (250 ml) can of Red Bull, or 80 mg &mdash worsened performance on the reaction test.

Why does it take more oxygen to recover?

  • You needed to replace the oxygen the body needed but couldn’t get (oxygen deficit). and heart rate are elevated (to remove CO2) and this needs more oxygen.
  • Body temperature and the metabolic rate are increased and this needs more oxygen.
  • Adrenaline and Noradrenaline are increased which increases oxygen consumption.

So after exercise, there are other factors causing an increase in oxygen needs as well as repaying the lack of oxygen during exercise.

The chart above is often seen and shows how the amount of oxygen used by the body changes over time. In the beginning, the body works anaerobically leaving an oxygen deficit. Over time the oxygen consumption levels out to a steady-state. After exercise, the oxygen is paid back (oxygen debt). Notice the area of oxygen debt is greater than the area of oxygen deficit for the reasons stated above.


How are macro-evolutionary patterns in vertebrate brain structure best characterised, and what processes drive those patterns? Answering such questions requires understanding how developmental mechanisms or architectural constraints, as well as selection acting on neural traits, together shape and support behavioural and cognitive evolution. Debates over these conflicting pressures on variation have dominated vertebrate evolutionary neurobiology for decades, with no unified theoretical framework in sight.

At the heart of this debate are two views of vertebrate brain evolution which, at their most polarised, make seemingly opposing predictions while both appearing logically sound and empirically supported. Under one hypothesis, brain components are developmentally coupled such that the size of each component is largely determined by common developmental mechanisms, such as the schedule, timing and duration of neurogenesis [1,2,3]. This would lead to the majority of brain structures evolving in a ‘concerted’ manner, with the size of separate components being closely predicted by overall brain size [1,2,3,4]. Initially, this coupling was discussed as a potential evolutionary constraint, associated with ‘spandrels’ whereby late developing brain regions such as the neocortex, may have expanded disproportionately as a by-product of architectural constraints, before later being co-opted functionally [2]. Proponents of this hypothesis now largely argue that developmental coupling is a mechanism that evolves in response to selection favouring conservative scaling, and is, as such, a potential adaptive mechanism rather than a constraint per se [1, 3]. However, the view that concertedness in itself indicates developmental constraint remains widespread in the literature (e.g. [4,5,6,7,8,9,10,11,12]).

A contrasting hypothesis instead argues that variation in brain components is largely developmentally independent of both other brain structures, and of total brain size, allowing them to respond to targeted selection pressures in a ‘mosaic’ way [13,14,15,16,17]. Mosaic evolution is often discussed as facilitating neural adaptations, reflected in non-allometric changes in brain structure, but it also invokes stabilising selection to otherwise maintain scaling relationships between co-evolving, functionally interdependent brain components [14, 18]. In essence, the mosaic model favours ‘external’ explanations that emphasise the role of both divergent and coordinated selection in driving both independent phenotypic evolution and co-variation of brain structures, while ‘concerted’ theorists stress ‘internal’ mechanisms which emphasise the role of developmental coupling as a route to maintaining scaling relationships [19].

Perhaps confusingly, both hypotheses have at times been supported by analyses of the same volumetric data (e.g. [2, 14, 20]). Proponents of the ‘concerted’ view of brain evolution pointed to consistent allometric scaling between brain components and total brain size as evidence of strong developmental integration across brain structures [1, 2, 4]. Proponents of the ‘mosaic’ model instead pointed towards co-evolution between brain components that is independent of total brain size, and evidence for ‘grade shifts’ that indicate deviations in scaling between taxonomic groups, as evidence that brain components are caught between distinct selection pressures, and constrained from functional interdependence [14]. Distinctions between these hypotheses have become more nuanced, with the concerted hypothesis incorporating periodic restructuring of the brain, accommodating some mosaic change [3, 21]. But, regardless, universally satisfactory tests of the generality of these hypotheses have proven elusive, there is frequent confusion in the literature between the distinction between patterns and mechanisms of brain evolution, and little data exists on when one mechanism may be favoured over another.

There are two key reasons for this deadlock. First, proponents of concerted and mosaic models are engaged in a ‘relative significance debate’ [22]. Both sides agree that brain evolution exhibits features associated with both concerted and mosaic evolution, but disagree on which pattern dominates across evolutionary time, and why (see for example, [1], p. 299). Relative significance makes hypothesis testing difficult. Neither hypothesis is subject to critical tests, as both accommodate—and even expect—different degrees of departure from the ‘norm’. Alternative views of brain evolution therefore run the risk of being too indeterminate for definitive testing.

Second, tests of these hypotheses are underdetermined by available evidence. Although proponents of both mechanisms can point to support from developmental data (reviewed in [18, 23])—showing, for example, how concerted patterns of brain evolution can be produced by changes in the regulation of neural progenitor cell proliferation [24,24,25,27], or how changes in the allocation, rate or duration of cell division among the cell populations that lead to specific regions can produce mosaic changes in brain structure [28,28,29,31]—these data are naturally less readily available than volumetric data, and therefore, tests of generalisation are limited. As such, empirical support for concerted or mosaic evolution is most often drawn from comparative analyses of volumetric brain data. These data reflect the outcome of the interaction between competing adaptive and constraining factors and do not, in themselves, provide evidence of the developmental mechanisms involved [32, 33]. This is a critical point, as ‘concertedness’ has frequently become a byword for developmental constraint (e.g. [4,5,6,7,8,9,10,11,12, 34]), potentially biasing the interpretation and presentation of many studies. However, the mosaic brain hypothesis also predicts co-variation between interdependent brain regions. If the brain is viewed as a network of interdependent networks, these functional constraints could produce consistent scaling relationships across brain components — i.e. concerted evolution — without invoking developmental coupling [18]. As inferred through classic evolutionary theory [35], merely recognising a concerted pattern is insufficient evidence to assess alternative mechanisms, or to support the predominance of either hypothesis.

If patterns of phenotypic variation alone are unsuitable for identifying the mechanisms that underpin allometric scaling, what evidence could? As noted by previous authors, ‘it is not the phenotypic correlation that matters, so much as the genetic correlation’ [36]. Although brain morphology can be highly plastic, responding to effects of the physical or social environment, which may alter the appearance of how brain structures scale within species (e.g. [37, 38]), the majority of comparative studies interrogating patterns of brain evolution implicitly assume these effects are small relative to heritable variation. Quantitative, intra-specific genetic studies provide a test of this assumption and of the relative strength of genetic correlations between brain size and structure. Several recent quantitative genetics studies have found evidence of substantial genetic independence between brain components [5, 8, 39], a central prediction of the mosaic brain hypothesis (reviewed in [18]). However, these studies typically concern standing genetic variation within populations. The developmental coupling hypothesis can accommodate this evidence if much of this genetic variation is mildly deleterious and is maintained in the population due to negative selection being weaker than drift, for example. If this was the case, selection for changes in brain structure or brain size may more frequently act on de novo mutations that are distinct in their developmental effects compared to standing genetic variation, and which are generally purged from the population during times of evolutionary stasis in brain structure, perhaps because they have larger fitness effects. If this were the case, intra-specific studies might not reflect the genetic architecture favoured by selection over evolutionary timescales. Currently, we have insufficient evidence either way. At a comparative level, some authors also argue that both concerted and mosaic patterns are observed in their data, with pairs of structures evolving in a coordinated, or concerted, manner, potentially supported by direct mechanisms linking their development, while others evolve independently [7, 40,39,42]. This would invoke complex patterns of developmental integration that occur after the major brain divisions are established [40], rather than the more global developmental integration suggested by previous authors, but the limited attempts to test this using molecular data do not currently support this idea [43]. Hence, neither phenotypic data nor currently available genetic data are sufficient to unite views on the relative importance of developmental and functional coupling, constraint and adaptive lability in the evolution of brain structure.

When faced with relative significance and empirical underdetermination, simple mathematical models can help realise basic causal dynamics in a ‘bare-bones’ system and are a way of examining the dependencies between variables that are thought to be important. We can envision ‘bare-bones’ models as tools that serve to make explicit the assumptions and reasoning involved in otherwise linguistic arguments, sometimes revealing previously hidden assumptions [44, 45]. While they lack empirical data, and must therefore be treated with care, they can be critical for informing future empirical studies and aiding the interpretation of existing literature [46]. This is particularly true for relevant significance debates which lack a straightforward way to weigh the importance of multiple mechanisms in different contexts using empirical data. Here, a modelling approach can be used to explore how key variables behave, which can dovetail with existing experimental or comparative studies, or prompt new ones. This approach has recently been applied to debates over the socio-ecological selection pressures shaping brain size [47,46,47,50], providing a new approach to the field of evolutionary neurobiology. Here, we introduce an agent-based model of brain structure that allows us to explore the interactions between fitness and constraints derived from selection, development and function (summarised in Additional file 1: Figure S1). In particular, our model allows us to formalise several verbal arguments over the role of developmental coupling in brain evolution specifically, we ask:

Do functional dependencies produce concerted patterns of evolution as well as developmental coupling (e.g. [32, 33])?

Can both mechanisms be adaptive (e.g. [1])?

Do the costs of neural tissue select against concertedness when selection acts on a specific brain component (e.g. [51])?

Is developmental integration evolutionarily labile (e.g. [52]), and do functional dependencies select for developmental coupling (e.g. [32, 52])?

Does stabilising selection or constraint on brain size lead to increased frequencies of mosaic evolution (e.g. [51])?

Our model allows us to explore these previously verbal arguments and interpretations of volumetric data. We demonstrate that this ‘bare-bones’ model helps clarify current debates surrounding the evolution of brain structure by capturing the basic evolutionary dynamics at play, and hope that it shifts these debates in a productive theoretical and empirical direction.

Brain scans reveal 'gray matter' differences in media multitaskers

Simultaneously using mobile phones, laptops and other media devices could be changing the structure of our brains, according to new University of Sussex research.

A study published today (24 September) reveals that people who frequently use several media devices at the same time have lower grey-matter density in one particular region of the brain compared to those who use just one device occasionally.

The research supports earlier studies showing connections between high media-multitasking activity and poor attention in the face of distractions, along with emotional problems such as depression and anxiety.

But neuroscientists Kep kee Loh and Dr Ryota Kanai point out that their study reveals a link rather than causality and that a long-term study needs to be carried out to understand whether high concurrent media usage leads to changes in the brain structure, or whether those with less-dense grey matter are more attracted to media multitasking.

The researchers at the University of Sussex's Sackler Centre for Consciousness used functional magnetic resonance imaging (fMRI) to look at the brain structures of 75 adults, who had all answered a questionnaire regarding their use and consumption of media devices, including mobile phones and computers, as well as television and print media.

They found that, independent of individual personality traits, people who used a higher number of media devices concurrently also had smaller grey matter density in the part of the brain known as the anterior cingulate cortex (ACC), the region notably responsible for cognitive and emotional control functions.

Kep kee Loh says: "Media multitasking is becoming more prevalent in our lives today and there is increasing concern about its impacts on our cognition and social-emotional well-being. Our study was the first to reveal links between media multitasking and brain structure."

Scientists have previously demonstrated that brain structure can be altered upon prolonged exposure to novel environments and experience. The neural pathways and synapses can change based on our behaviours, environment, emotions, and can happen at the cellular level (in the case of learning and memory) or cortical re-mapping, which is how specific functions of a damaged brain region could be re-mapped to a remaining intact region.

Other studies have shown that training (such as learning to juggle, or taxi drivers learning the map of London) can increase grey-matter densities in certain parts of the brain.

"The exact mechanisms of these changes are still unclear," says Kep kee Loh. "Although it is conceivable that individuals with small ACC are more susceptible to multitasking situations due to weaker ability in cognitive control or socio-emotional regulation, it is equally plausible that higher levels of exposure to multitasking situations leads to structural changes in the ACC. A longitudinal study is required to unambiguously determine the direction of causation."

    'High media multi-tasking is associated with smaller gray-matter density in the anterior cingulate cortex' by Kep Kee Loh and Dr Ryota Kanai is published in Plos One on 24 September 2014

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

Is there a link between brain's energy consumption and human experience? - Biology

Optional Breathing: Activating the Diaphragm
The everyday experiences of breathing for most untrained individuals is much more inconsistent than one would assume. Practices in yoga often first teach individuals to observe their own breathing to ultimately familiarize the student with the sensations of respiration. Thus, one meaningful aspect in learning breathing techniques is the awareness in the difference in smooth, even breathing to erratic breathing. Modifications in respiratory patterns come naturally to some individuals after one lesson, however, it may take up to six months to replace bad habits, and ultimately change the way one breathes (Sovik, 2000). The general rule, often noted in studies, and particularly observed by Gallego et al. (2001) was that if a voluntary act is repeated, “learning occurs, and the neurophysiological and cognitive processes underpinning its control may change.” Gallego et al. continue that while some changes can be made, the need for longer-term studies is warranted to better understand the attention demanding phases involved with these breathing changes.

Although the diaphragm is one of the primary organs responsible for respiration, it is believed by some yogics to be under functioning in many people (Sovik, 2000). Thus, there is often emphasis placed upon diaphragmatic breathing, rather than the use of the overactive chest muscles. Anatomically the diaphragm sits beneath the lungs and is above the organs of the abdomen. It is the separation between cavities of the torso (the upper or thoracic and the lower or abdominal). It is attached at the base of the ribs, the spine, and the sternum. As describe earlier, when the diaphragm contracts the middle fibers, which are formed in a dome shape, descend into the abdomen, causing thoracic volume to increase (and pressure to fall), thus drawing air into the lungs. The practice of proper breathing techniques is aimed at eliminating misused accessory chest muscles, with more emphasis on diaphragmatic breathing.

With diaphragmatic breathing the initial focus of attention is on the expansion of the abdomen, sometimes referred to as abdominal or belly breathing. Have a client place one hand on the abdomen above the navel to feel it being pushed outward during the inhalations. Next, the breathing focus includes the expansion of the rib cage during the inhalation. To help a student learn this, try placing the edge of the hands along side the rib cage (at the level of the sternum) correct diaphragmatic breathing will elicit a noticeable lateral expansion of the rib cage. Diaphragmatic breathing should be practiced in the supine, prone and erect positions, as these are the functional positions of daily life. Finally, the diaphragmatic breathing is integrated with physical movements, asanas, during meditation and during relaxation. Analogous to the seasoned cyclist, who is able to maintain balance effortlessly while cycling, the trained practitioner in diaphragmatic breathing can focus attention on activities of daily life while naturally doing diaphragmatic breathing. To summarize, Sovik suggests the characteristics of optimal breathing (at rest) are that it is diaphragmatic, nasal (inhalation and exhalation), smooth, deep, even, quiet and free of pauses.

Answers to Some Common Questions on Breathing
The following are some answers to common questions about breathing adapted from Repich (2002).
1) How do you take a deep breath?
Although many people feel a deep breath comes solely from expansion of the chest, chest breathing (in of itself) is not the best way to take a deep breath. To get a full deep breath, learn how to breathe from the diaphragm while simultaneously expanding the chest.
2) What happens when you feel breathless?
Breathlessness is often a response of your flight or fight hormone and nervous system triggering the neck and chest muscles to tighten. This makes breathing labored and gives a person that breathless feeling.
3) What is hyperventilation syndrome?
Hyperventilation syndrome is also known as overbreathing. Breathing too frequently causes this phenomenon. Although it feels like a lack of oxygen, this is not the case at all. The overbreathing causes the body to lose considerable carbon dioxide. This loss of carbon dioxide triggers symptoms such as gasping, trembling, choking and the feeling of being smothered. Regrettably, overbreathing often perpetuates more overbreathing, lowering carbon dioxide levels more, and thus become a nasty sequence. Repich (2002) notes that this hyperventilation syndrome is common in 10% of the population. Fortunately, slow, deep breathing readily alleviates it. The deliberate, even deep breaths helps to transition the person to a preferable diaphragmatic breathing pattern.
4) When you feel short of breath, do you need to breathe faster to get more air?
Actually, just the opposite. If you breathe fast, you may start to over breathe and lower your carbon dioxide levels. Once again, slow deep diaphragmatic breathing is recommended.
5) How do you know if you are hyperventilating?
Often times a person does not realize when he/she is hyperventilating. Usually more focus is centered on the anxiety-provoking situation causing the rapid breathing. With hyperventilation there is much more rapid chest breathing, and thus the chest and shoulders will visibly move much more. As well, if you take about 15-17 breaths per minute or more (in a non-exercise situation) then this could be a more quantifiable measure of probable hyperventilating.

Final Thoughts
The research is very clear that breathing exercises (e.g. pranayama breathing) can enhance parasympathetic (inhibit neural responses) tone, decrease sympathetic (excitatory) nervous activity, improve respiratory and cardiovascular function, decrease the effects of stress, and improve physical and mental health (Pal, Velkumary, and Madanmohan, 2004). Health and fitness professionals can utilize this knowledge and regularly incorporate proper slow breathing exercises with their students and clients in their classes and training sessions.

Side Bar 1. What is Asthma? And Five Common Myths Associated with it?
The word "asthma" is derived from the Greek word meaning "to puff or pant.” Typical symptoms of asthma include wheezing, shortness of breath, chest tightness, and a persistent cough. Asthma attacks develop from an involuntary response to a trigger, such as house dust, pollen, tobacco, smoke, furnace air, and animal fur.
Asthma provokes an inflammatory response in the lungs. Airway linings swell up, the smooth muscle surrounding them contracts and excess mucus is produced. Airflow is now limited, making it hard for oxygen to get through to the alveoli and into the bloodstream. The severity of an asthma attack is determined by how restricted the airways become. When an asthmatic's airways become chronically inflamed it takes only a slight trigger to cause a major reaction in the airways. Oxygen levels can become low and even life threatening. Below are some of the common myths about asthma.
Myth 1) Asthma is a mental disease
Because asthma sufferers often have attacks when facing emotional stress, some people have identified it as a psychosomatic condition. Asthma is a real physiological condition. However, emotional stimuli can act as an asthma trigger, worsening an asthma flare up.
Myth 2) Asthma is not a serious health condition
Quite the contrary! Asthma attacks may last several minutes or go on for hours. With extended asthma agitation one’s health is increasingly threatened. Indeed, if an airway obstruction becomes severe, the sufferer may experience respiratory failure, leading to fainting and possible death.
Myth 3) Children will grow out of asthma as they mature to adulthood
The majority of asthma sufferers will have it for life, although some people do appear to grow out of it.
Myth 4) Asthmatics shouldn’t exercise
Asthmatics can and should exercise. Importantly they should find the types of exercise they feel most comfortable w ith as well as the best place and time to do the exercise.
Myth 5) Not that many people are affected by asthma
According to National Center for Health Statistics (2002), 20 million people suffer from asthma in the U.S. Asthma can be life threatening as it took the lives of approximately 4,261 deaths in 2002. Researchers are unclear if this is due to improper preventative care, chronic overuse of asthma medications, or a combination of both factors.

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Gallego, J., Nsegbe, E. and Durand, E. (2001). Learning in respiratory control. Behavior Modification, 25 (4) 495-512.

Guz, A. (1997). Brain, breathing and breathlessness. Respiration Physiology. 109, 197-204.

Jerath, R., Edry J.W, Barnes, V.A., and Jerath, V. (2006). Physiology of long pranayamic breathing: Neural respiratory elements may provide a mechanism that explains how slow deep breathing shifts the autonomic nervous system. Medical Hypothesis, 67, 566-571.

National Center for Health Statistics. (2002). U.S. Department of Health and Human Services. Centers for Disease Control and Prevention.

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Alcohol Research & Health. 200327(2): 143-145.

Roger F. Butterworth, Ph.D., D.Sc.

Roger F. Butterworth, Ph.D., D.Sc., is scientific director of the Neuroscience Research Unit at CHUM (Hôpital Saint–Luc), and professor of medicine at the University of Montreal, Montreal, Canada .

Alcohol’s harmful effects on liver cells not only interfere not only with the normal functioning of the liver but also impact distant organs, including the brain. Prolonged liver dysfunction resulting from excessive alcohol consumption can lead to the development of a serious and potentially fatal brain disorder known as hepatic encephalopathy (HE). Patients with HE suffer from sleep disturbances, changes of mood and personality, severe cognitive effects (e.g., a shortened attention span), psychiatric conditions such as anxiety and depression, as well as motor disturbances, including motor incoordination and a type of flapping tremor of the hands called asterixis. In the most serious cases, the patients no longer respond to external stimuli and may fall into a coma (i.e., hepatic coma), which can be fatal.

Analyses of brain tissue of HE patients found characteristic changes in the structure of supporting cells known as astrocytes rather than obvious destruction of nerve cells (i.e., neurons). Astrocytes are large star–shaped cells, distributed throughout the brain, that help maintain the proper composition of the fluid surrounding the neurons. For example, astrocytes take up brain chemicals (i.e., neurotransmitters) that are released by neurons, and minerals such as potassium, which are generated and secreted during the brain’s energy metabolism. In addition, astrocytes eliminate some substances that are toxic to neurons (i.e., neurotoxic). The proper functioning of the astrocytes and their interactions with the neurons are essential to brain function. Patients with HE frequently have pairs and triplets of abnormal astrocytes with a characteristic structure known as Alzheimer type II astrocytosis, in which the astrocytes’ nuclei are enlarged and glassy–looking. This glassy appearance is caused by the fact that the DNA and its associated proteins are confined to the edges of the nuclei, rather than distributed throughout them. Alzheimer type II astrocytes also exhibit other physiological and functional abnormalities.

Diagnosing HE in alcoholic patients is difficult because no single clinical or laboratory test can conclusively establish the diagnosis. Patients frequently are misdiagnosed, particularly in the early stages of HE, when symptoms such as euphoria, anxiety, depression, and sleep disorders occur that are common to a number of psychiatric conditions. In addition, whether—and to what extent—a patient shows each of these symptoms depends on fluctuations in the patient’s medical status or diet. Diagnosis also is hindered because HE can be triggered or exacerbated by a medical procedure known as the transjugular intrahepatic stent shunt (TIPS), which commonly is used to treat alcoholic patients who experience elevated blood pressure in the portal vein that transports blood to the liver. By redirecting blood flow around the liver, the TIPS procedure is intended to alleviate this condition and prevent complications such as gastrointestinal bleeding and accumulation of fluid in the abdomen (i.e., ascites).

Relationships Between the Liver and the Brain

Normal brain functioning depends on several aspects of normal liver functioning. For example, the liver supplies certain nutrients to the brain that the brain itself cannot produce. The liver also cleanses the blood of substances that could damage brain cells (i.e., neurotoxins). Although the brain is protected from many neurotoxic substances by the blood–brain barrier—a property of blood vessels in the brain that prevents passage of many compounds from the blood into the brain tissue—certain neurotoxins can penetrate that barrier. These substances—which include ammonia, manganese, and other chemicals—can enter the brain at least to some extent unless they are effectively removed from the blood by the liver.

In patients with fibrosis or cirrhosis (whether caused by excessive alcohol consumption or factors such as viruses or toxins), the liver loses its capacity to remove toxic substances from the blood because the number of functional liver cells (i.e., hepatocytes) has decreased. Moreover, in these patients some of the blood that normally flows through the portal vein into the liver for cleansing is diverted directly into the general circulation without first passing through the liver, a phenomenon known as portal–systemic shunting. As a result, the shunted blood is not detoxified and blood levels of toxic substances rise. Persistently elevated neurotoxin levels damage brain cells and the patients begin to develop HE. In fact, studies involving neuropsychological tests have found that although alcohol’s direct effects on the brain also cause cognitive deficits and brain damage in alcoholics, HE is a major contributing factor to cognitive dysfunction in alcoholics with severe liver disease. In these studies, alcoholic patients with cirrhosis had significantly lower scores on learning and memory tests than did alcoholics without cirrhosis, indicating that liver dysfunction is associated with more extensive brain dysfunction in these patients (Tarter et al. 1993).

Mechanisms Leading to HE

Researchers have gained a better understanding of the mechanisms leading to HE in patients with alcoholic liver disease by using neuroimaging and spectroscopic techniques that permit them to study the metabolism and functions of specific brain regions in living patients. These studies have confirmed the contributions of at least two neurotoxic substances, ammonia and manganese, to the development of HE.

The Role of Ammonia. Some of these investigations employed positron emission tomography (PET), a technique used to examine the metabolic activity of various body regions, including the brain, by monitoring the transport and breakdown of radioactively labeled molecules using sophisticated detection devices. Some PET studies of alcoholic patients have assessed ammonia uptake and metabolism in the brain. In cirrhotic patients with mild HE, PET analyses using radioactive ammonia have revealed significant increases in the amount of ammonia taken up and metabolized in the brain (Lockwood et al. 1991). In particular, a variable called the permeability–surface area product (PS), a measure of how much ammonia can enter the brain from the general circulation, increases as cirrhotic patients start to develop HE. When the PS increases, a greater proportion of the ammonia in the general circulation can enter the brain.

The brain has only a limited capacity to remove any ammonia coming in because of the increased PS. The only way to eliminate any ammonia that has reached the brain cells is through a reaction mediated by an enzyme called glutamine synthetase, which is found in the astrocytes. This enzyme combines a molecule of the amino acid glutamate with a molecule of ammonia to form the amino acid glutamine. In patients with HE, the amounts of glutamine formed in the brain are correlated with the severity of the disease, indicating that the brain is exposed to increasing levels of ammonia as the disease progresses (Lockwood et al. 1997 Butterworth 2002).

Ammonia adversely affects both neurons and astrocytes. Because the enzyme that eliminates ammonia in the brain is present only in astrocytes, neurons are virtually defenseless against increased ammonia concentrations and therefore are likely to suffer ammonia–related damage. For example, ammonia has deleterious effects on nerve signal transmission that is mediated by numerous neurotransmitter systems (Szerb and Butterworth 1992) and impairs the brain’s energy metabolism. In addition, ammonia can alter the expression 1 of various genes that encode key brain proteins involved in the brain cells’ energy production, structure, and cell–to–cell interactions. ( 1 The term “gene expression” refers to the entire process of converting the genetic information encoded in a gene into a protein product.) These alterations in gene expression may account for some of the changes in neurotransmitter activity and astrocyte structure observed in HE patients.

The Role of Manganese. Researchers also have used magnetic resonance imaging (MRI) to analyze changes in the brains of alcoholics. This technique generates images based on differences between tissues in water content as well as in the content of other molecules that respond to a magnetic field. MRI analyses have found that more than 80 percent of alcoholics with cirrhosis show regions of abnormally high signal intensity (i.e., signal hyperintensities), primarily in a brain area called the globus pallidus, which is involved in control of motor function (Lockwood et al. 1997 Spahr et al. 2000). The intensity of these signals correlates with the presence of certain signs and symptoms of impaired motor function but not with the patients’ performance on tests assessing global encephalopathy and cognitive functioning.

Additional analyses have determined that hyperintense MRI signals in the globus pallidus are probably caused by manganese deposits in that region (Lockwood et al. 1997). Indeed, studies using brain tissue from alcoholic cirrhotic patients who died from HE have revealed manganese levels in the globus pallidus that were up to seven times higher than manganese levels in subjects without cirrhosis (Butterworth et al. 1995). Manganese normally is eliminated by the joint actions of the liver, gallbladder, and bile ducts (i.e., the hepatobiliary system), but patients with chronic liver failure have elevated manganese concentrations in the blood. As a result, the metal can enter the brain and be deposited in the globus pallidus and associated brain structures, where it particularly affects the actions of certain proteins (i.e., receptors) that interact with the neurotransmitter dopamine. This effect is demonstrated by the fact that dopamine receptors are altered in the brains of alcoholic cirrhotic patients who died in a hepatic coma (Mousseau et al. 1993). In addition, manganese induces Alzheimer type II changes that interfere with the functioning of astrocytes. Thus, manganese deposits in the globus pallidus may account for both the motor symptoms and the structural changes in astrocytes that are characteristic of HE.

Treatment of Patients With HE

Researchers and clinicians are exploring various approaches to preventing HE in patients with alcohol–induced chronic liver failure or to ameliorating its consequences. These approaches include the following:

Strategies to lower ammonia levels. One approach—administering certain sugar molecules (e.g., lactulose) or antibiotics (e.g., neomycin)—reduces the production of ammonia in the gastrointestinal tract. Other strategies are intended to increase the conversion of ammonia into harmless molecules outside the brain—for example, by treating the patients with an agent called L–ornithine L–aspartate, which helps to incorporate ammonia into the amino acid glutamine in the skeletal muscle—and to bolster the residual ability of the patient’s cirrhotic liver to eliminate ammonia as urea.

Neuropharmacological strategies. These approaches involve using neuroactive drugs to counteract ammonia’s harmful effects on neurotransmitter systems in the brain. This type of treatment is in its infancy, however, because researchers have not yet identified the precise nature of the neurotransmitter systems that contribute to the development of HE or are affected by the condition.

Liver–assist devices. These machines, or “artificial livers,” are dialysis systems composed of columns that are filled with hepatocytes, a protein called albumin, charcoal, or combinations thereof. The patient’s blood is circulated through these columns to remove the toxins. In initial studies, patients treated with an albumin–based system showed lower amounts of ammonia circulating in the blood as well as improvements in the severity of their encephalopathy (Mitzner and Williams 2003).

Liver transplantation. This approach is widely used in alcoholic cirrhotic patients with end–stage chronic liver failure. In general, implantation of a new liver results in significant improvements in cognitive function in these patients (Arria et al. 1991) and corrects the excessive ammonia levels as well as the MRI signal hyperintensities that result from manganese deposits found in patients with HE (Pujol et al. 1993).

HE is a serious complication of alcoholic liver disease that contributes to cognitive dysfunction in chronic alcoholic patients. In patients with HE, the damaged liver can no longer remove neurotoxic substances such as ammonia and manganese from the blood. As a result, these molecules may enter the brain, where they can exert a variety of harmful effects that interfere with normal neurotransmitter activity, impair motor functions, and cause structural alterations in the astrocytes. To prevent or treat HE in alcoholic patients with cirrhosis, physicians currently rely primarily on strategies to lower blood ammonia concentrations as well as on liver transplantation in patients with end–stage liver disease new approaches also are also being investigated.

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