As vast as our universe is, so are its complexities. One of the most complex of objects in it remains the human brain, an organ which when fully grown requires 750 millilitres of oxygenated blood every minute to maintain normal activity – of the total amount of oxygen delivered to the body’s tissues by the arteries, 20 % is consumed by the brain which only makes up 2% of the body’s weight. It also has 100 billion neurons with each connected to 7000 others, leading to a surprising 700 trillion connections. This complexity is far from excessive as we study the importance of the construction of the brain for civilisation and all life on our planet. This fascinating organ is not only at the basis of low-level biological tasks such as heart rate monitoring, respiration and feeding, but it is also vital in the evolution of our behaviours for survival (e.g. perceiving, learning and making rapid decisions). At the heart of human existence, it is also the organ allowing the human organism to explore higher abilities unique to its kind such as thoughts, emotions, consciousness and love.
While nearly 50% of the Central Nervous System and Peripheral Nervous System are neurons, they are supported by glial cells. The ratio of Neurons to glial cells in the human brain is close to 1:1 (Azevedo et al., 2009) and glial cells come in 3 important types:
Firstly, astrocytes [also known as ‘star cell’] produce chemicals needed for neurons to function such as extracellular fluid, provide nourishment [linked to blood vessel] and clean up dead neurons. They also help keep the neuron in place.
Secondly, oligodendrocytes support the axon by creating a myelin coating which increases the speed and efficiency of axonal conduction [in the PNS myelin is produced by Schwann cells].
Thirdly and lastly, microglia works with the immune system by protecting the brain from infections while also being responsible for inflammation in cases of brain damage.
Neurons are cells that are devised to ensure the reception, conduction, and transmission of electrochemical signals and come in several types depending on their structure and function. The 3 main types are Multipolar, Bipolar and Unipolar neurons.
Most neurons in the brain are multipolar, and these have many extensions from their body: one axon and several dendrites. Bipolar neurons have two extensions: one consisting of dendrites and one of axon and are typically specialised sensory pathways (e.g. vision, smell, sight and hearing). Unipolar neurons are cells with a single extension (an axon) from their body and are mostly somatosensory (e.g. touch, pain, temperature, etc). Although existing in variety, all neurons perform the same overall function: to process and transmit information.
The neuron is composed of three main parts, firstly the cell body [also known as the ‘soma’] is a primary component of the neuron that integrates the inputs received by the neurons to the axon hillock. The body or soma is between 5 and 100 microns in diameter (a micron is one-thousandth of a millimetre) surrounded by a membrane and hosts the cytoplasm, the nucleus and a number of organelles. The cytoplasm resembles jelly-like substances and is in continuous movement, with the nucleus containing the genetic code of the neuron that is used for protein synthesis (e.g. of some types of neurotransmitters). The neuron’s metabolism is dependent on the organelles that perform chemical synthesis, generate and store energy; and provide the structural support (similar to a skeleton) for the neuron.
Secondly, we have the dendrites [derived from Greek ‘Dendron’] which are branched cellular extensions emanating from the cell body that receive most of the synaptic contacts from other neurons. It is important to note that dendrites only receive information from other neurons and cannot transmit any of it to them; their purpose is to propagate information to the axon.
Thirdly, axons which can measure from up to a few millimetres to one metre in length, transmit information from the soma to other neurons, ending with the terminal buttons which store chemicals used for inter-neuron communication. There are 2 types of axons. The first type – myelinated axons – are covered with a fatty, white substance known as myelin which is a sheath that has gaps at places known as the nodes of Ranvier. Myelin acts as a catalyst in making electric transmission faster and more efficient by insulating the axon. Hence, with myelinated axons, myelin is vital for effective electric transmission, and its loss leads to serious neurological diseases such as multiple sclerosis, The second type of axons are not covered by myelin, resulting in a slower electric transmission.
Neurons are always active, even when no information is being received from other neurons, and must feed themselves (through blood vessels), maintain physiological parameters within a certain range (homeostasis), and maintain their electrical equilibrium, which is essential in the transmission of information.
The terminal buttons [also known as Axon terminals] are button-like endings of the axon branches which release the information to other neurons via neurotransmitter molecules through synaptic vesicles stored within itself. The neurotransmitter is then diffused across the synaptic cleft [gap between 2 membranes] where a depolarisation from incoming action potentials lead to the opening of Calcium channels and Ca+ triggers vesicles to fuse with pre-synaptic membrane, releasing the neurotransmitter into the synaptic cleft which diffuses across and binds with receptors of the next neuron’s post-synaptic membrane’s receptors; causing particular ion channels to open.
Post synaptic potentials further defines the opening credentials. Excitatory Post Synaptic Potential (EPSP) is the result of depolarisation (+ve) which increases the positive charge after allowing Sodium (Na+) ions inside. Another result could be an Inhibitory Post Synaptic Potential (IPSP) which would be caused by the hyperpolarisation (-ve) due to the opening of Chloride (Cl-) channels. The summation carried out by the Axon Hillock calculates whether it reaches the threshold, if it does; an Action Potential in the Postsynaptic Neuron is triggered and excess neurotransmitter is taken back by the pre-synaptic neuron and degraded by enzymes.
The Neural Signature of Learning
Learning is the process through which memories are formed and it is assumed to be the result of enduring changes in the synapses between neurons – a mechanism called long-term potentiation (LTP), which is the strengthening of connections between two neurons by the synaptic chemical change. Memory storage is the strengthening or weakening of synaptic connections. Hebbian learning is a key principle for long-term potentiation (LTP): “neurons that fire together, wire together” (Hebb, 1949), meaning that any two cells or system of cells that are repeatedly active at the same time will tend to become ‘associated’ – and recent studies seem to also suggest that the growth of new synapses foster learning. A new memory is a change to the nervous system as a result of learning, i.e. a memory is the internal representation of knowledge acquired through experience.
New experiences change the nervous system, a phenomenon known as “neuroplasticity”. One solid example of this process of neuroplasticity is given in the study done by Maguire et al. (2000): where the volume of the hippocampus [an area of the brain essential for learning & memory] of London Taxi Drivers were compared with that of a control group, with the hypothesis that extensive experience with spatial navigation and resulting increase in spatial memory might have led to enduring changes in the brain. Eventually, as predicted the hippocampal volume of the London Taxi Drivers was significantly larger than the normal people in the control group. Furthermore, the hippocampal volume in the taxi drivers correlated positively with the amount of time spent on the job. From such an experiment, it was deduced that new experiences can still change the nervous system in adulthood.
Hebb argued convincingly that enduring changes in the efficiency of synaptic transmission were the basis of long-term memory. If we assume that the repetition of a reverberatory activity induces lasting cellular changes that adds to its stability when an axon of Cell A is near enough to excite a Cell B and repeatedly takes part in its activation, some growth process or metabolic change takes place in one or both cells such that Cell A’s efficiency as one of the cells activating Cell B is increased.
Scientific evidence for Hebb’s law has been repeatedly found, i.e. when a neuron fires, an action potential travels to the end of the axon, where synaptic vesicles release neurotransmitters into the synaptic cleft, these neurotransmitters bind to the postsynaptic receptors on dendrite and trigger an action potential in the next neuron. The strength of such a synaptic connection between neurons is not fixed, but depends on the amount of postsynaptic receptors, the sensitivity of the postsynaptic receptors and the amount of neurotransmitters released by the presynaptic neuron. Correlated activity of presynaptic and postsynaptic neurons result in an increase in the strength of this synaptic connection between neurons, known as long-term potentiation [first observed by Terje Lomo in 1966]. This is the neural signature of learning.
A neuron codes information through its “spiking rate” [response rate] which is the number of action potentials propagated per second. Some neurons may have a high spiking rate in some situations (e.g. during speech), but not others (e.g. during vision), while others may simply have a complementary profile. Neurons that respond to the same type of information are generally grouped together, this leads to the functional specialisation of brain regions. The input a neuron receives and the output that it sends to another neuron is related to the type of information a neuron carries. For example, information about sounds is only processed by the primary auditory cortex because this region’s inputs are from a pathway originating in the cochlea and they also send information to other neurons involved in a more advanced stage of auditory processing (e.g. speech perception). For example, if it were possible to rewire the brain such that the primary auditory cortex was to receive inputs from the retinal pathway instead of the auditory pathway (Sur & Leamey, 2001), the function of that part of the brain would have changed [along with the type of information it carries] even if the regions themselves remained static [with only inputs rewired]. This is worthy of being noted as when one considers the function of a particular cerebral region: the function of any brain region is determined by its inputs and outputs – hence, the extent to which a function can only be achieved at a particular location is a subject open to debate.
Gray matter, white matter and cerebrospinal fluid
Neurons in the brain are structured to form white matter [axons and support cells: glia] and gray matter [neuronal cell bodies]. The white matter lies underneath the highly convoluted folded sheet of gray matter [cerebral cortex]. Beneath the white matter fibers, there is another collection of gray matter structures [subcortex], which includes the basal ganglia, the limbic system, and the diencephalon. White matter tracts may project between different regions of the cortex within the same hemisphere [known as association tracts) and also between regions across different hemispheres [known as commissures; with the most important being the corpus callosum]; or may project between cortical and subcortical regions [known as projection tracts]. A number of hollow chambers called ventricles also form part of the brain, these are filled with cerebrospinal fluid (CSF), which serves important functions such as carrying waste metabolites, transferring messenger signals while providing a protective cushion for the brain.
Reflections: From biology to psychology
In the classic essay on the “Architecture of Complexity”, Simon (1996) noted that hierarchies are present everywhere at every level in natural systems – taking the field of physics as an example, in particular the way elementary particles form atoms, atoms form molecules, and molecules form more complex entities such as rocks. Furthering this metaphor as an example, we may also wish to look at the organisation of a book: letters, words, sentences, paragraphs, sections and finally chapters.
In biological systems, a similar type of hierarchical structure can be found at many levels, particularly in the way the brain is organised. Simon seems to convincingly argue that complex systems’ evolution would have had to have benefited from some degree of stability, which is precisely enabled by hierarchical organisation. The main idea is that hierarchical organisations typically have a degree of redundancy – that is, the same functions at the particular level can be carried out by different components; and if one component fails, the system is only slightly affected since other components could perform the functions to some extent. Systems that lack systematic hierarchical organisation tend to lack this degree of flexibility, and a system as complex as the human brain must have a strong hierarchical organisation, or it would not have been able to evolve into such a complex organ.
Using the Limbic system [diagram above] as an example of each level’s specialisation, it is possible to understand how it is responsible for a particular set of functions related but also separate from other parts of the brain. The Limbic system is essential in allowing the human organism to relate to its environment based on current needs and the present situation with experience gathered. This very intriguing part of the brain may in fact be the source of – what many might call – “Humanity” in man as it is responsible for the detection and subsequent expression of emotional responses. One of its parts, the amygdala is implicated in the detection of fearful or threatening stimuli, while parts of the cingulate gyrusare involved in the detection of emotional and cognitive conflicts. Another part, the hippocampus is of major importance in learning and memory; it lies buried in the temporal lobes of each hemisphere along with the amygdala. Other structures of the Limbic system are only visible from the ventral surface [underside] of the brain; the mamillary bodies are two small round protrusions that have traditionally been implicated in memory (Dusoir et al., 1990), while the olfactory bulbs are located under the surface of the frontal lobes with their connections to the limbic system underscoring the importance of smell for detecting environmentally salient stimuli (e.g. food, animals, cattle, cars, etc) and its influence on mood and memory.
One of the main insight of Simon’s analysis is that scientists should be thankful to nature for the existence of hierarchies, since they make the task of understanding the mechanisms involved easier. It can be achieved by simply focusing on one specific level rather than trying to understand the phenomena in all its complexities – because each level has its own laws and principles. On initial approximation, what happens at lower levels may end up being averaged without taking into account all the details and the happenings at the higher levels, which may unfairly be considered as constant.
Focusing on a popular example, we could look at the biologist and naturalist Charles Darwin when he formulated his theory of evolution. At that time, the structure of DNA [which would be discovered 70 years later] was not a major concern of his, furthermore the latter did not have to consider the way the Earth came to exist. Instead, what the biologist did was to focus on an intermediate level in the hierarchy of natural phenomena (e.g. primates, animals, birds, insects, etc): how species evolved over time. Such example also seems to illustrate a vital point in this analysis: the processes involved at the level we are interested in can be understood by analysing the constraints provided by the levels below and above. What happens at the low levels (e.g. the biochemical level) and what happens at high levels (e.g. the cosmological level) limit how any species evolve; and if the biochemistry of life had been disrupted, and if our planet did not provide the appropriate environmental elements and conditions for life to flourish, evolution would simply not have happened. As science progresses and shatters many outdated perspectives at looking at life & nature on planet Earth, links are being made between these different levels of explanation.
It is now firmly accepted among intellectuals from evidence gathered in Biopsychology (also known as Neuroscience) that the acquisition of skills is dependent on an organism’s ability to learn and develop throughout its lifetime, and DNA is an important factor at the biochemical level for the transmission of heredity traits postulated by Charles Darwin. Hence, human evolution is a process that is continuous, multifaceted, complex, creative & ongoing; and intelligent design [e.g. psychological, educational, linguistic, biological, genetic, philosophical, environmental, dietary, etc] is an undeniably important factor for the intelligent evolution of human societies.
- Azevedo, F.A.C., Carvalho, L.R.B., Grinberg, L.T., Farfel, J.M., Ferretti, R.E.L., Leite, R.E.P., Jacob Filho, W., Lent, R. & Herculano-Houzel, S. (2009) Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. Journal of Comparative Neurolology , 513 , 532-541.
- Dusoir, H., Kapur, N., Byrnes, D. P., McKinstry, S., & Hoare, R. D. (1990). The role of diencephalic pathology in human-memory disorder-evidence from a penetrating paranasal brain injury. Brain , 113 , 1695-1706.
- Gobet, F., Chassy, P. and Bilalic, M. (2011). Foundations of cognitive psychology. 1st ed. New York: McGraw-Hill Higher Education.
- Hebb, D. O. (1949). Organization of behaviour. NJ: Wiley and Sons.
- Lomo, T. (2003). The discovery of long-term potentiation. Philosophical Transactions of the Royal Society B: Biological Sciences, 358(1432), pp.617-620.
- Maguire, E., Gadian, D., Johnsrude, I., Good, C., Ashburner, J., Frackowiak, R. and Frith, C. (2000). Navigation-related structural change in the hippocampi of taxi drivers. Proceedings of the National Academy of Sciences, 97(8), pp.4398-4403.
- Pinel, J. (2014). Biopsychology 8th ed. Harlow: Pearson.
- Simon, H. A. (1996). The sciences of the artificial (3rd edn). Cambridge: The MIT Press.
- Sur, M. & Leamey, C. A. (2001). Development and plasticity of cortical areas and networks. Nature Reviews Neuroscience , 2 , 251-262.
Updated: 15th of June 2018 | Danny J. D’Purb | DPURB.com
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