- 1. Introduction.
Since the Big Bang, the age of the observable universe is estimated to be 13.75 (±0.11) billion years [see Larson, Dunkley, Hinshaw et al., 2010] and the age of our planet, Earth, has been consistently estimated to be approximately 4.5 (±0.05) billion years [see also Gunter, 1986]. The question often arises as to the conduciveness of the world, and universe, in which we live to the formation of organic life. Looking back to the way in which we hypothesize the universe was formed can be advantageous when considering self-assembly and the process of evolution. Just 10-45 seconds following the big bang the fundamental forces (e.g., the electro-magnetic force, and gravity) became present. Between 10-35 seconds and 10-5 seconds the strong and weak nuclear forces arose and formed the first matter (e.g., the quarks, protons, and neutrons). And after 1 second electrons began to form. 380,000 years after the big bang the universe was cool enough for hydrogen and helium nuclei to capture electrons and become stable atoms [for review see Christian, 2011]. Just like the evolution of this early universe—which has gradually changed and evolved over billions of years—the story of the evolution of the human brain can be traced back billions of years, to the beginning of our universe.
1.1 Foundations on which to build a brain…
We can readily see that our universe seems to provide a number of distinct advantages and disadvantages in terms of facilitating the evolution of organic life. Some characteristics of our universe that would not appear to be advantageous for the development of carbon-based organic life would include: (1) the temperature of the universe being near absolute zero (3 °K; -454 °F); (2) only about 4.3% of the mass in the universe is mass that we can see, the rest of the mass is still very unknown (e.g., dark matter); (3) the distribution of measurable mass is extremely sparse. For example, only a few hydrogen atoms per cubic meter exist in space, whereas the air we breathe contains about 1025 molecules per cubic meter. Finally, (4) the universe is so rapidly expanding that we will soon loose the ability to infer that all of the mass was at one point centrally contained [for review see Krauss, 2009]. However, there are a number of attributes about our universe, and our planet earth in particular, that would seem ideal for the development of organic life: (1) the chemical components of organic life are relatively common. The universe is, and almost always has been, about 75% hydrogen and 24% helium; additionally, the compounds that make organic life possible have relatively stable configurations of protons as well as a higher occurring abundance due to their relative simplicity [i.e., low numbers of protons exist in organic elements; and these elements have common and stable isotopic variations: 12C, 13C, 14N, 15N, 16O, 17O, 18O, 23Na, 24Mg, 25Mg, 26Mg, 31P, 35Cl, 37Cl, 39K, 41K, 40Ca, 42Ca, 43Ca, 44Ca]; (2) hydrogen has an organic attraction to electronegative atoms such as fluorine, oxygen, and nitrogen [Parthasarathi, Subramanian & Sathyamurthy, 2006]. The development of water (H2O) in a universe that is 75% hydrogen is therefore much more probable. And if there were a planet with moderate temperatures (from ≈ 32°F to 212°F) then we would expect to see H2O existing in a liquid state (ℓH2O). Additionally, these high probability hydrogen bonds are responsible for the behavior of a number of essential features of more complex life forms; for example, the double helix structure of deoxyribonucleic acid (DNA) is partly made possible by the interactions of the hydrogen bonds between their associated nitrogenous bases [e.g., guanine, cytosine, thymine, and adenine; Aldaye, Palmer & Sleiman, 2008]. The chemical characteristics of these elements were the foundation and subsequent architecture for the complexity and diversity of terrestrial organic life.
Operating under the assumption/understanding that our universe—specifically, our solar system and planet—offered fertile grounds for the development of organic life, there are still a number of issues that must be addressed to more completely understand the amount of complexity and diversity we see around us. For example, the gradual progression of more advanced nervous systems requires the consideration of a number of specific organism level demands; demands which are uniquely placed on larger multicellular organisms, and are, thus, generally avoided by more simple unicellular organisms. To the contrary, there are also a number of demands that are uniquely placed on more simple unicellular organisms that are generally avoided by larger multicellular organisms. Therefore, the primary aim of this discussion will be developing a scientific and biological understanding of nervous system evolution with respect to the current naturalistic understanding of evolution.
- 2. Reproduction, Mutations, and Natural Selection
The question of how any particular ‘thing’, organic or inorganic, came to be can be divided into two parts: first, how did it originate? And second, from the time of its origin, how did it persist? The second part of this question, however, is infinitely simpler than the first: every organism on this planet persists because it has a chain of reproductively successful ancestors. The issue of origination is substantially more complex, but there are a number of basic ways that a reproductive organism could come into existence: (1) spontaneous origin would refer to a reproductive organism coming to exist by way of a sudden arrangement of materials; (2) a new reproductive organism could have a modified origin via the partial modification of a previously existing organism; finally, (3) two organisms could join together in order to, symbiotically, create a new reproductively capable organism. The idea of spontaneous origin is difficult to address as the issue of complexity elicits problems—namely, the more complex the organism the less likely it is that all of the constituent pieces would have come about at one instant. However, as we are not going to discuss the ‘origin of Life’, the modified and symbiotic origination theories are going to be more relevant in evaluating the most probable route by which simple organisms became increasingly more complex.
A critical component to the theory of evolution that is intimately tied to reproduction is the heritability of modifications and the distinction between genotypic and phenotypic changes. It has been established that for any species to persist, they must have the ability to reproduce. However, only specific changes can be passed between generations via genetic information. An example of phenotypic change would be cutting off the tail of a mouse; it has been shown that changes to an organism’s phenotype are not going to be passed to its offspring [see Weismann, 1889]. As a result, the only way for modifications to be transferred between generations is by making changes to the genotype—most commonly referred to as mutation. However, not all mutations are heritable (or advantageous). Most of the cells that make up a reproductive organisms body—called somatic cells—are not able to make changes to the organism’s genome. Although somatic cells (e.g., skin cells, muscle cells, kidney cells, etc.) do continue to divide (via mitosis) throughout the lifespan, they do not have the ability to generate cells capable of reproducing. Consequently, somatic cell mutations (e.g., skin cancer) are not going to be heritable. Germ-line mutations, on the other hand, are changes in the cells that are responsible for organism reproduction (i.e., gametes like sperm and egg cells) and can be passed between generations. All organisms have a basic genotype and phenotype; genetic information passes between generations by way of reproduction. An organism’s phenotype will change across its lifetime through the continuous changing of the rate at which the genotype expresses particular genes. Evolutionarily speaking, the information within a specific genotype will direct the way that a continuously developing phenotype progresses. In other words, whether genetic information encoded within a genotype makes it to the next generation is partially dependent on what sort of phenotype it builds (i.e., genotypes that build a really strong phenotype will have a higher probability of reproducing).
The development of an evolutionarily advantageous phenotype, by way of ideally expressing ones genotype, is the critical factor behind the idea of natural selection—the process by which biological traits become more or less frequent in a population of organisms based on the positive or negative influence the traits have on the reproductive ability of the population in question [e.g., “…if any one species does not become modified and improved in a corresponding degree with its competitors, it will soon be exterminated.”; see Darwin, 1859]. Again, this advantageous phenotype will have a higher probability of reproducing; the natural consequence of a process of more selective reproduction is that “modified traits” are naturally selected over “ancestral traits” only if they are more advantageous than the existing ancestral traits. However, common sense tells us that this is going to be a rare occurrence. The logic follows like this: if an ancestral trait has been advantageous for many generations within a particular group of organisms, the probability that a modification will make that trait even more advantageous is going to be quite small [see Temme, 2007].
Even considering the competitive nature of natural selection, the very low probability of advantageous mutations, and the difficulty involved in reproduction, the mechanisms of electrically based communication systems (i.e., nervous systems) have flourished across species. The reason for the universal—across species—application of nervous systems has everything to do with the positive and significant correlation between organism size and organism complexity.
- 3. Prokaryotic Cells to Eukaryotic Cells…RNA to DNA…Unicellular to Multicellular…
As we begin to consider the evolution of spectacularly complex organisms, the foundation of our discussion must be predicated on understanding the origin and persistence of more simple organisms. Prokaryotic cells are, for the most part, unicellular organisms [for review see Sapp, 2005]. Additionally, it has been suggested that single-celled prokaryotes evolved from membrane bound organic molecules as early as 1 billion years following the formation of the Earth itself [Schopf, Kudryavtsev, Agresti, Wdowiak & Czaja, 2002; Wilde, Valley, Peck & Grahm, 2001]. And as early as 1.9 billion years after the formation of the Earth, evidence suggests that the ratios of stable isotopes (e.g., 13C, 15N, 16O, 23Na, 24Mg, 31P, etc.) allowed for the existence of an abundance of simple organisms, including a number of different species of photosynthetic organisms [see Archer & Vance, 2006; Cavalier-Smith, Martin & Martin, 2006; Hayes & Waldbauer, 2006; Johnson, 2011; Summons, Bradley, Jahnke & Waldbauer, 2006]. There is a high probability that these early organisms were not composed of DNA. The current hypothesis is that these early organisms were ribonucleic acid (RNA) based [Gilbert, 1986]. RNA and DNA are very similar molecules, and RNA is even capable of storing information in much the same way as DNA; however, there are two primary differences worth noting: (1) RNA uses the nitrogenous base, uracil (where DNA uses thymine); and (2) RNA has additional 2′ hydroxyl-groups which make the molecule slightly more unstable (prone to hydrolysis) than its “more advanced deoxyribose-cousin” [see Fohrer, Hennig & Carlomagno, 2006]. Both the 2′ hydroxyl groups and the uracil substitution contribute to the inherent instability of RNA, particularly when the molecule becomes larger. Thus, RNA could never have supported the evolution of larger and more complex organisms; as it is the case that RNA is simply not physically capable of storing the large amount of information needed to build a more complex organism [e.g., the DNA-based human genome contains @2.9 billion deoxyribose nucleotide base pairs, whereas the RNA-based human immunodeficiency virus (HIV) only contains 9,749 ribose nucleotide base pairs; Lander & Linton et al., 2001; Ratner & Haseltine et al., 1985].
Apart from limited RNA based information storage, early prokaryotes faced another significant challenge: a challenge related to becoming larger¾physically. Two physical realities kept early prokaryotes restricted to maintaining smaller sizes: (1) these cells depend on simple diffusion; and (2) as cells get larger, the amount of surface unit volume decreases. The problem with diffusion is that as materials spread over a certain distance, time increases in proportion to the square of the distance (i.e., time a distance2). For example, it has been estimated that oxygen (O2) can diffuse ten micrometers (mm) in 1/100th of a second [Brogioli & Vailati, 2001]. If we use the earlier established proportion, we can approximate how long it would take for a molecule of O2 to move a distance of one millimeter (mm): 1mm is 100 times greater than 1mm; therefore, it will take approximately 100×100 (1002 = 10,000) times longer to move the same quantity of O2. In order to move 1mm, the same amount of O2 will take 100 seconds [10,000*(1/100) seconds]. We can easily extrapolate that diffusion places obvious restrictions on organism size, as it would be impossible for larger organisms to transfer nutrients, or communicate messages by which to generate movement in response to the environment. To more clearly elaborate this restriction, if our circulatory system were based on diffusion it would take a molecule of oxygen over 3 years to travel 1 meter (m) from our lungs to our feet [1m = 1,000mm; therefore it would take 1,0002 times longer to move 1m vs. 1mm; 1,0002(100 seconds) = 100,000,000 seconds to move 1m]. The second reason for prokaryotic size restriction is based on restricted surface area. Any cell which wants to become larger, and potentially more complex, will need to increase size in two basic ways: (1) increased volume (which dictates the rate a cell needs to process molecules for energy); and (2) increased surface area (which dictates the rate a cell is able to bring the molecules in and out through diffusion or transport). So, the question becomes: what is the relationship between volume and surface area? We can better understand this question if we examine the relationship between surface area (SA) and volume (n) in a series of spheres with increasing radii (r = 2, 3, 4, and 10). We can obtain the corresponding surface area (SA = 4pr2 = 16p; 36p; 64p; 400p) as well as the corresponding volume of each sphere respectively (n = 4/3pr3 @ 10.67p; 36p; 85.33p; 1,333.33p). As we can see, the relationship between surface area and volume is not a linear one. In fact, volume increases exponentially faster than surface area. This is because increasing volume is a cubic function (n a x3), whereas increasing surface area is a squared function (SA a x2). Thus, as cells get larger the demand for resources (based on cellular volume) will increase exponentially faster than the ability a cell has to obtain resources (based on the surface area available to transport resources in, and get waste out); essentially, large prokaryotic cells would starve to death.
3.1 Eukaryotic/Multicellular Organism Evolution
Eukaryotic cells, which are approximately 2.1 billion years younger than prokaryotic cells, evolved efficient mechanisms to navigate around some of the problems encountered by the prokaryotic cells; although, eukaryotes encountered a number of specific problems of their own [for age approximation see Bengtson, Belivanova, Rasmussen & Whitehouse, 2009; Knoll, Javaux, Hewitt & Cohen, 2006]. This ‘sudden’ evolution of eukaryotic cells seemed to progress exponentially¾and almost inevitably¾toward the endpoint of larger organisms. Due to the presence of a very rigid cell wall in prokaryotic cells, the evolution of eukaryotic cells likely began with the development of a more flexible outer membrane. In fact, one of the most fundamental differences between the prokaryotes and eukaryotes is the loss of this rigid cell wall [see Sapp, 2005].
This critical development allowed for eukaryotes to avoid the previously mentioned size-based, prokaryotic-specific problems relating to surface area and diffusion. Additionally, eukaryotic cells developed superior mechanisms to gather nutrients as well as generate energy. Many prokaryotic cells use(d) diffusion to obtain nutrients from their environment, where as a eukaryotic cell is able to perform endocytosis in order to more efficiently break down nutrients. This ability to invaginate a flexible membrane proved to be the first distinct evolutionary advantage over the ancestral prokaryotic cells: (1) this decreased the surface area to volume ratio that had previously been problematic [SA a x2:n a x3]; (2) cells now have the ability to sequester DNA inside of a membrane bound nucleus for greater protection of information; and (3) the ability to perform endocytosis also resulted in the, mutually beneficial, symbiotic merging of these early eukaryotic organisms, with a simpler prokaryotic organelle as an endosymbiont [i.e., endosymbiosis; the way mitochondria potentially came to exist inside our cells; Johnson, 2011]. And considering our original hypothesis of the relationship between increased size and increased complexity, the inclusion of organelles that are capable of performing tasks independently of their “hosts” would be extremely advantageous in the reallocation of some tasks [e.g., generating adenine tri-phosphate; Mulkidjanian, Makarova, Galperin & Koonin, 2007; Rak, Gokova & Tzagoloff, 2011] in order for the cell to focus on the performance of other tasks (e.g., becoming larger and increasing complexity).
The transition from unicellular prokaryotic organisms to unicellular eukaryotic organisms to multicellular eukaryotic organisms brings some more evidence to the idea of size being positively correlated with complexity. Just like a non-rigid membrane in eukaryotes, becoming multicellular allowed for a huge increase in species size, complexity, and diversity. Although it was the case that the development of eukaryotic cells subverted a number of the biological problems that were faced by the prokaryotes, the eukaryotic cells faced a number of specific problems of their own. However; staying in line with the hypothesis that larger organisms are often more complex organisms, increasing size does seem to come with a number of irrefutable advantages in terms of increased organism complexity and a greater species diversification. We will see, however, that the specific problems that are introduced in larger organisms are problems that culminate in the development of very elaborate nervous systems.
- 4. Why Do Big Things Need/Have Neurons/Neurotransmitters to Communicate?
As previously stated, the problems with prokaryotic cells centered around the fact that they were restricted with regards to size. This size based restriction lead to a corollary restriction with regards to complexity. The foundation of multicellular organisms rest on a redistribution of resources at both the cellular level, as well as the organism level. At the cellular level, a major portion of the foundation of multicellular evolution was the change from the prokaryotic cell wall to the flexible eukaryotic lipid-based membrane. The prokaryotic cell wall was rigid in order to avoid osmotic problems (i.e., the cell has higher levels of solutes inside versus outside and H2O will tend to rush in and equilibrate; thus, killing the cell). Similarly, multicellular eukaryotic organisms have developed mechanisms to pump out certain ions that exist in abundance within the cell (e.g., ATP-based Na+/K+ pumps); it is the removal of these ions in order to account for the concentration gradient of solutes that lead to the current electrical gradient (e.g., resting potential) that is generated in the nerve cells of more complex organisms.
In order to more fully understand why complex organisms use electrically based systems to communicate (i.e., nervous systems and action potential), we must consider the alternative methods: (1) diffusion; (2) DNA and protein synthesis (3) circulatory based control; (4) hormone regulated signaling; or, potentially, (5) neuropeptide control. First, the problems with diffusion-based communication have been made readily apparent, as it was a major restriction on organism complexity (however, we will discuss paracrine-based signaling between neurons). DNA contains all of the information needed to make the enzymes the body uses to catalyze reactions and DNA polymerase can replicate DNA at amazing speeds [106,000 pages of nucleotides per hour; see Schwartz & Quake, 2009]. However, widespread protein communication is not realistic due to the complexity and frequency of the messages that need to be sent. For example, the synthesis of proteins is an extremely laborious process, and if a cell had to be constantly generating proteins in order to communicate messages to other cells it would be a very biologically taxing process [see chapter in Sadava, Heller, Hillis & Berenbaum, 2009]. The problems with communication through circulatory systems, and the inherent problem with hormone/endocrine level control, is that (1) it is relatively slow compared to neurons, and (2) the system itself suffers from a lack of specificity (i.e., hormones get dumped into the blood stream, the blood stream goes everywhere; one can imagine all of the muscles in the body contracting at the same time). Finally, another option that our brains do use is complex neuropeptide control (e.g., endorphins, enkephalins, and insulin). The problem with neuropeptides is that they are complex strings of amino acids that require lots of calcium (Ca2+) to release, and once released we have to go back to the DNA in order to generate new ones.
4.1 Developing and Using Neurons…Does Diffusion Work?
Neurons offer an evolutionary release from all of those other communication problems, and at the same time they also regulate the cells osmotic environment. The basis of the nervous system is that muscles are wired into our body in such a way that we can generate responses to incoming stimuli by eliciting movement in a location that is not adjacently located. This communication is made possible by a number of unique features, including: (1) the ability to make direct connections between cells that recognize environmental change, and cells that generate a response to environmental change; (2) the critical use of an electrically-based system that uses neurotransmitters to communicate; and perhaps most importantly, (3) the generation of a communication system that is capable of learning.
The critical component to nervous system design is the basic architecture of the neuron. Neurons are able to extend very long axons (up to 1m) in order to connect with target locations; for example, the sciatic nerve, the longest and largest nerve in the body, runs from the sacral plexus region of the spine to the big toe on each foot and is 3/4 of an inch in diameter [see Eidelson, 2010]. If the soma of the sciatic nerve is approximately 100mm, given the 1m length of the axon this is roughly equivalent to putting a balloon with a diameter of 1ft onto a string that is 2.07 miles long. The chemical communication system in the nervous system of humans (and other organisms) is able to use neurotransmitters; this is critical for a number of reasons. First, neurotransmitters are very simple, biosynthetically, to produce. For example, the catecholamines comprise a number of common neurotransmitters in the human body that are all simply slight variations on each other’s component structure. Phenylalanine is a dietary amino acid, which is hydroxylated (given a hydroxyl group; -OH) by the enzyme phenylalanine hydroxylase and turned into tyrosine. Tyrosine is then hydroxylated to become L-Dihydroxy-phenylalanine (L-DOPA). L-DOPA looses a carboxyl group (COOH) to become dopamine. The enzyme Dopamine b-hydroxylase adds a hydroxyl group (-OH) to Dopamine to create norepinephrine [see Joh & Hwang, 1987]. Essentially what this means is that the body is able to generate neurotransmitters in a, biosynthetically, ‘quick-and-dirty’ kind of way; in fact, nearly all neurotransmitters are recycled; for example, the amine-based neurotransmitters are all readily broken down, presynaptically, by an enzyme called monoamine oxidase (MAO; see Edmondson, Mattevi, Binda & Hubálek, 2004).
The nervous system of larger, more complex, organisms is able to generate rapid and coordinated responses based on its use of neurons. As previously mentioned, neurons are cells that are able to create a communication link between the cells in the body that are able to recognize environmental change (e.g., the human retina and visual processing system), and the cells in the body that are able to generate an organism level response to the information in the environment (e.g., the legs of an organism being told to move in response to the visual identification of a threat). The beauty of a system that is wired this way is that reflexes are possible—if a certain stimulus occurs, then a certain response will occur. These types of reflexes, or ‘response hierarchies’ [e.g., Temme, 2007], are the foundation for the generation of a nervous system that is capable of learning from its environment. When generating these ‘response-based hierarchies’ neurons are able prioritize activity based on previous experience. Specifically, the nervous system is structured in such a way that a specific environmental stimulus will elicit the same response from the nervous system of a particular organism. Although these types of ‘reflexive responses’ are a critical component to the evolution of learning, they are not what separate humans from the rest of the complex multicellular organisms. Voluntary motion is one of the neural activities that is critical in our evolution. This premise of voluntary motion is that a part of an organism has made a distinct change from simply reacting to actually generating action. The ability for any organism to generate a future plan of action [e.g., frontal lobe activity; Stuss & Knight, 2002] would not be possible without the ability to do more than simply generate reactions to environmental stimuli.
As previously stated, diffusion was highly problematic with regards to the prokaryotic cells becoming more advanced; however, the paracrine system in the human brain operates under the rules of simple diffusion. The most obvious question then becomes: if diffusion-based restrictions lead to the maintained simplicity of the prokaryotes, how could it possibly operate successfully in the human brain? The paracrine system is responsible for the communication between a presynaptic neuron and a postsynaptic neuron. The distance between the two is estimated to be approximately 20 nanometers (nm), which is equivalent to 20 billionths of a meter (20 x 10-9 m) [Drachman, 2005]. The human brain is estimated to contain roughly 500 trillion synapses; additionally, every centimeter of the human cerebral cortex contains roughly one billion individual synapses [see Alonso-Nanclares, Gonzalez-Soriano, Rodriquez & DeFelipe, 2008]. The reason neurotransmitter diffusion is successful at the synapse level is due to the small (20nm) size of the synapse itself—if it would take O2 1/100th seconds to diffuse 10mm (1.0 x 10-5 m), neurotransmitters could potentially diffuse across a 20nm (2.0 x 10-8 m) synapse in 1/1,000th the time (1/50,000th of a second). It is obvious that diffusion is able to work very well at the paracrine/neurotransmitter level; however, one has to wonder if the complexity of the system itself is able to explain our broad spectrum of advanced cognitive capabilities.
- 5. Brain Size, Neuronal Volume and Ideal Organism Complexity
It certainly seems as though evolution and selective mutation have sculpted the human brain into an ideal processor of information and an ideal response generator. The average human brain (1,350 g) contains approximately 86.1 (±8.1) billion neurons [Azevedo, Carvalho, Grinberg, Farfel, Ferretti, Leite, Filho, Lent & Herculano-Houzel, 2009; Pakkenberg, Pelvig, Marner, Bundgaard, Gundersen, Nyengaard & Regeur, 2003], and the number of non-neuronal glial cells has been speculated to be anywhere from 10 to 50 times the number of neurons [Nishiyama, Yang & Butt, 2005]. Incidentally, some recent comparative research suggests that the ratio of glia to neurons may fluctuate as a function of location [see Azevedo et al., 2009]. The structure and organization of the neurons¾specifically the synapses between those neurons¾is what gives rise to the extreme complexity and diversity both within humans as well as between species. What is typically thought of when considering organism complexity is the relationship between cortical volume and overall brain weight; for example, the cortex of the rodent is quite large relative to its brain size when compared to that of an alligator [see Nieuwenhuys, Donkelaar & Nicholson, 1998]. What makes the human brain much more advanced is, very similar to the way eukaryotic cells developed, the invagination of cortical space. The human cortex is highly convoluted, which increases the amount of surface area per unit of volume (i.e., packing in more neurons to the same amount of space). But are more neurons better?
5.1 What is so great about 100 billion?
The relationship between brain size and body size has been important when considering the organization of complex life. One may consider that the number of neurons, and the ratio of cortical surface area to unit of volume are critical factors in determining ideal nervous system functioning. However, we also have to consider what it takes to energetically maintain such an advanced system. It is known that the human brain comprises only about 2% of the bodies weight, but the brain receives 15% of cardiac output, uses 20% of total body O2, and 25% of all of the bodies glucose (C6H12O6). Furthermore, within normal levels of cerebral blood flow, the brain extracts about 50% of the O2 from the arterial hemoglobin, and 10% of the glucose from the arterial blood [for review see Zauner & Muizelaar, 1997]. Additionally, it has been estimated that neurons consume about 75% of all O2 in the central nervous system, 80% of all energy (ATP) generated by the body is used in order to maintain ion gradients in neurons, and glial cells (which make up 50% of the brains volume), only account for about 10% of total cerebral metabolism—indicating how critical neurons are in the energy metabolism hierarchy of the brain [see Siesjö, 1984]. In fact, a surplus of neurons in Caenorhabditis elegans (C elegans), caused by a mutation that blocks apoptosis, results in no behavioral deficits in moving or reproducing [Ellis & Horvitz, 1986]; however, it has been show that the reproductive capacity of mutant nematodes (e.g., C elegans) with a 20% increase in total neuron number (due to decreased apoptosis) is 15-30% below normal [Ellis & Horvitz, 1986; Williams & Herrup, 1988]. Further suggesting that increasing numbers of neurons may require an increased allocation of resources.
5.2 So…What is next?
The question of where we go from here is a critical one. Evolution, through natural selection, has shaped the human brain into one of the most spectacular pieces of machinery in the known universe. For example, the total number of possible combinations between the synapses in the human brain [(1.23 x 1014)!] is estimated to be greater than the total number of atomic particles in the known universe (≈ 3 x 1076). More realistically, a 3.4g copper (Cu64) penny contains 32 quintillion (≈ 3.2 x 1022). Additionally, it has been estimated that the human brain operates at approximately 24.5 quadrillion (≈ 2.45 x 1016) operations per second. It seems as though the human brain operates at peak efficiency all of the time. However, we must also consider that evolution is an ever-present process and that we are always changing.
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 The theory of the Big Bang is the prevailing cosmological theory of the early development of our observable universe.
 A phenotype is any observable characteristic or trait of an organism.
 The genotype is the genetic makeup of an organism.
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