Category: Neuroplasticity

Chapter six, Brain Lock Unlocked, Using Plasticity to Stop Worries, Obsessions, Compulsions, and Bad Habits from the text “The Brain That Changes Itself” is the topic of choice for this paper. Neuroplasticity is an intriguing subject and so is the idea of using it as a treatment for neurological disorders through talk therapy. This talk therapy is able to rearrange the brain and improve a disorder. Neuroplasticity is the ability of the nervous system to respond to intrinsic and extrinsic stimuli by reorganizing its structure, function, and connections. It occurs during early development can occur later in life in response to the environment. Chapter six focuses on plasticity-based therapy for obsessive-compulsive disorder (OCD); however, this therapy can be used and has been used for many more disorders that don’t already have a successful treatment in place. The two articles chosen review the effectiveness of neuroplasticity as a therapy option for patients with Schizophrenia and brain damage.

Brain Lock Unlocked

Obsessive-compulsive disorder (OCD) is among the worst of anxiety disorders. Medications alleviate symptoms, but do not eliminate them. OCD often worsens over time, gradually altering the structure of the brain. A patient with OCD may try to get relief by giving in to his compulsion, but the more he focuses on it, the worse it gets (Doidge, 2007, p. 117).

Typical obsessions consist of fears like being contaminated by germs or chemicals, or being obsessed with symmetry. The concerns don’t usually make sense and the patient understands this, but they still can’t help the feeling and must act on it. When a person tries to resist a compulsion it consumes them, but if they act on it to get temporary relief, this only encourages negative behavior and enhances the disorder.

OCD has been very difficult to treat. Medication and behavior therapy are only partially helpful for many people (Doidge, 2007, p. 119). The most common treatment for OCD is called ‘exposure and response prevention,’ a form of behavior therapy that helps about half of OCD patients make some improvement, though most don’t get completely better. Another form of therapy, Cognitive Therapy, is based on the premise that problematic mood and anxiety states are caused by cognitive distortions, inaccurate or exaggerated thoughts (Doidge, 2007, p. 122).

Jeffrey M. Schwartz developed an effective talking therapy that could change the brain. Through plasticity-based treatment, a patient’s brain is able to normalize. The caudate nucleus, our brain’s ‘automatic gearshift”, sits deep in the center of the brain and allows our thoughts to flow from one to the next unless, as happens in OCD, the caudate becomes extremely ‘sticky’ and the caudate doesn’t ‘shift the gear’ automatically, and thoughts get stuck. Schwartz wondered whether patients could shift the caudate ‘manually’ by paying constant, effortful attention and actively focusing on something else pleasurable. This approach makes plastic sense because it ‘grows’ a new brain circuit that gives pleasure and triggers dopamine release which, as we have seen, rewards the new activity and consolidates and grows new neuronal connections. This new circuit can eventually compete and weaken the older one. This treatment will basically replace bad behaviors with better ones (Doidge, 2007, pp. 120-121).

Once a patient has acknowledged that the worry is a symptom of OCD, the next crucial step is to refocus on a positive, pleasurable activity and “shift” the gear manually the moment he becomes aware he is having an OCD attack. This will assist in growing new circuits and altering the caudate. ‘The struggle is not to make the feeling go away; the struggle is not to give in to the feeling’. The goal is to resist the OCD sympton by ‘changing the channel’ to a new activity for as long as possible. Any time spent resisting is beneficial and that effort is what appears to create new circuits. Schwartz has had good results with by using his method in combination with antidepressants. The medication functions like training wheels on a bike, by lowering the anxiety enough for patients to benefit from the therapy and some patients don’t even need it to start with (Doidge, 2007, p. 123).

A Case Study on Promoting Neuroplasticity in a Patient with Schizophrenia

Current studies indicate that neuroplasticity-based cognitive training in schizophrenia has shown improvement in verbal learning/memory and cognitive control. This article focuses on the case study of a male diagnosed with Schizophrenia. The strategies used included cognitive remediation, physical exercise, and sleep. Cognitive remediation focuses on problems of memory, executive function, language, and attention and functional outcome. Such benefits result in improved behaviors, problem-solving, reduced symptoms and occupational outcome, therefore better recovery for people with schizophrenia. Physical activity improves learning and memory function in the hippocampus, releases neurotrophins that facilitate neuronal growth, and uses synaptic plasticity to promote brain health (Puskar, Slivka, Lee, Martin, & Witt, 2015, pp. 2-3).

The subject in this study used three coping techniques to manage his symptoms; deep breathing, basic T’ai Chi movements, and wearing headphones. T’ai Chi concentrates on relieving the physical effects of stress on the body and mind. The subject reported he never experienced hallucinations during T’ai Chi class. The use of headphones was to override hallucinations and act as a distraction until they lessened or were ignored. The coping strategies seemed to help the subject “shift gears” manually. This treatment lasted for 1 year with continuous improvement. These three approaches highlighted the unique role of neuroplasticity. Just like Schwartz’s therapy, the disease was explained to the patient in order for him to understand it and gain control of it. Understanding the brain and neuroplasticity enables alteration of neurocognitive functioning and adds to the patients toolkit of knowledge and behavioral skills to cope with the disease of schizophrenia (Puskar et al., 2015, pp. 4-5).

Harnessing Neuroplasticity: Modern Approaches and Clinical Future

This article reviews modern approaches of inducing neuroplasticity in patients or models of neurological disorders whereby neuroplasticity is known to be impaired, from neurodegeneration to traumatic brain injury and learning disability (Octavian Sasmita, Kuruvilla, & Pick Kiong Ling, 2018, p. 3). The nervous system could adapt and reorganize in cases of epileptic seizures, stroke and traumatic brain injuries; however, the degree of restoration varies. In addition to being effective, it is a marketable therapy due to it being low-cost, non-invasive, low-tech and non-drug (Octavian Sasmita et al., 2018, p. 8).

Induction of neuroplasticity has been a longstanding concept in neurorestoration. From molecular approaches to activity-dependent neuroplasticity. It has great potential in battling various neurological and neurodegenerative diseases. However, there needs to be careful consideration upon viewing neuroplasticity research as some are only symptom-curative. Neuroplasticity can possibly gain commercial success, but higher technology and more collaborative efforts are recommended (Octavian Sasmita et al., 2018, p. 10).

Neuroplasticity has been proven to be an effective treatment with some disorders, more research is needed to expand the benefits of neuroplasticity throughout various neurological disorders. However, previous studies do show positive effects and promise with this type of therapy. While searching for information on this topic I came across several therapeutic services/providers using this technique. This is just a few: The Center for Brain (offers therapy for ADHD, anxiety, learning disabilities, bipolar disorder, OCD, brain injury, etc.), The OCD Treatment Centre (offers therapy for OCD), Apex Brain Centers (offers therapy for addictions, brain injury, etc.). There were also several articles in support of this technique. This is a very interesting field and I look forward to learning more about it.

References

1. Doidge, M. (2007). The Brain That Changes Itself. Penguin Group.
2. Puskar, K., Slivka, C., Lee, H., Martin, C., & Witt, M. (2015). A Case Study on Promoting Neuroplasticity in a Patient with Schizophrenia. Perspectives in Psychiatric Care, 52, 95–101
3. Octavian Sasmita, A., Kuruvilla, J. & Pick Kiong Ling, A. (2018). Harnessing neuroplasticity: modern approaches and clinical future. International Journal of Neuroscience, VOL. 128, NO. 11, 1061–1077

How similar are the brains of London taxi drivers, United States Navy SEALs, and elite athletes? The answer: more similar than they seem at first glance. While they all perform drastically different tasks – from driving a car in a maze of a city, to combat in extreme circumstances, to cycling exceptional distances – their brains have metamorphized to be uniquely suited to the specific task which they perform at an elite level. The brains of elite performers optimize themselves for specific tasks through structural and functional changes brought about by consistent training over an extended period of time.

Neuroplasticity is the process of updating the brain structurally and functionally in response to specific experiences or needs. The study of this process began in the late 1700s and has experienced many changes in perception since. Modern instrumentation including MRI, functional MRI (fMRI), and electroencephalography (EEG) has opened new insights into the constant changes in the human brain.

To effectively review the topic of neuroplasticity in elite performers, a brief historical overview will be given. Then, the basic science behind neuroplasticity will be addressed. Last, three case studies of different groups will be evaluated with an integrated discussion of the neuroimaging methods which engendered these discoveries. The first case study of London taxi drivers will elucidate major structural plasticity. The second case study of Navy SEALs will examine functional plasticity to optimize performance. The third case study of elite athletes will demonstrate the symbiotic interplay of structural and functional plasticity. Sixty years ago, the scientific consensus was that the brain is a fixed and stable structure once an individual had reached adulthood. People believed that the brain contained a fixed number of cells, which represented the entire set of brain cells a person would ever have. In a sense, this is largely true. Most cells in the brain do not proliferate, but some do. The idea that the brain is a stable and fixed structure, however, is patently false. The brain is a dynamic and adaptive organ which updates itself to operate optimally under the set of conditions to which it is exposed. The idea that neuroplasticity occurs – that the brain changes both in terms of its size and its connections – is not new, but it has gone in and out of fashion.

The idea of neuroplasticity began in the 1780s with Malacarne’s experiments on the response of a dog’s brain to mental exercises. In the first half of the 1800s, Jean-Baptiste Lamarck proposed that the specific regions of the brain were specialized by performing certain tasks. In 1890, William James made the first true mention of plasticity in The Principles of Psychology (Costandi, 2016). Also in the 1890s, Spanish scientist Santiago Ramon y Cajal published papers stating that neurons compose the brain and he later hypothesized that changes could occur at the synapses (Costandi, 2016). About ten years later, however, he softened his position that the brain could be remodeled. In his famous textbook, Degeneration and Regeneration of the Nervous System, he stated that: “In the adult centers, the nerve paths are something fixed, ended and immutable. Everything may die, nothing may be regenerated” (J.G.G., 1929, & Costandi, 2016). This idea of stasis became the standard vein of thinking until the 1960s, when Hubel and Wiesel began their work on the developing brain (Costandi, 2016). Neuroplasticity is the brain’s ability to change or update itself to support different functions throughout the course of one’s life in response to changing demands and experiences. There are two broad subsets of neuroplasticity: functional plasticity and structural plasticity. Functional plasticity is any change in the physiological aspects of neurons (Costandi, 2016). A change in the basal firing rate of a neuron is an example of this. Structural plasticity encompasses any microscopic or macroscopic physical change to the brain (Costandi, 2016). Microscopic changes include the formation of new synapses, new dendrites, or increased myelination of axons. Macroscopic updates include a change in the size of certain lobes of the brain, for example.

It is now accepted that microscopic and macroscopic updates can occur at any stage of life, albeit to varying extents. The brain is most plastic during childhood, but adults can experience constructive or destructive changes. These changes can foster increased efficiency at a task; or, degradation can lead to diseases like dementia (Duong et. al., 2017). However, the focus of this review is neuroplasticity in elite performers, how these changes manifest themselves, and what advantages and disadvantages they yield.

The timescale on which macroscopic and microscopic changes vary. The formation or destruction of a synapse can occur in milliseconds. However, it can take hours to create or destroy dendrites. A new, functional synapse can be constructed in a few hours (Squire, 2014). The longevity of these changes depends on the duration and intensity of the stimulus. Stimuli include learning, stress, and training. The three following case studies delve into the manifestations of neuroplasticity induced by these stimuli. London taxi drivers have to memorize massive amounts of information and synthesize it on a regular basis to determine the fastest route between locations. Since this learning typically occurs after the age of eighteen, they provide an interesting subset of the population for studying neurological changes in an adult population. It takes anywhere from two to four years to learn the 25,000 streets and thousands of landmarks of greater London necessary to become a licensed cabbie (Transport for London, 2020). After this, prospective cabbies have to pass stringent tests to show they know the city and surrounding area of London and the fastest routes between landmarks. The failure rate is seventy percent. Those who pass boast a dramatic increase in the volume of grey matter in the hippocampal region of their brains.

A 2006 study compared the brains in a group of licensed London taxi-cab drivers to ordinary London bus drivers. The two groups were matched in age, handedness, and IQ. A whole-brain structural MRI scan was taken of each subject of the study using a 1.5 T magnetic field (Maguire et. al., 2006).

MRI is useful for examining the structural features of the brain owing to its high spatial resolution. In this study, 1 mm spatial resolution was achieved in the images. Protons cause a small magnetic field, and MRI harnesses this property to give a clear image of the brain. The subject is placed in a high external magnetic field in order to orient the spins of the species of interest in the same way. This orientation is called the bulk magnetization of the sample. The bulk magnetization is defined as “up,” so if a spin is opposite to this direction it is classified as “down.” To obtain an image of the sample, a radio frequency (RF) pulse is applied to excite a particular species in the sample. The RF pulse forces the nuclear spin axis from its equilibrium position. The relaxation of the sample is then measured and can be manipulated to provide an image of the sample. The relaxation of the sample is commonly characterized by T1 and T2 relaxation times in MRI. T1 relaxation, or spin lattice relaxation, is given by measuring the protons’ return to equilibrium by dissipating energy through elastic collisions or rotational energy loss. T2 relaxation, or spin-spin relaxation, is the relaxation of particles through the dephasing of spins of nearby protons. Taking the Fourier Transform of the data acquired gives the recognizable image of the brain.

The images collected by Maguire et. al. provided clear evidence of structural changes due to the intellectual demands of being a London cabbie. Compared to London bus drivers, taxi drivers showed significantly more gray matter volume in the mid-posterior hippocampus and less volume in the anterior hippocampal region (Maguire et. al., 2006). The hippocampus has been linked to many functions, particularly learning, spatial memory, and navigation. Interestingly, this trend of increased volume in the mid-posterior hippocampus and less volume in the anterior hippocampus followed a linear trend with the number of years driving a cab. There were no significant differences in the brains of bus drivers no matter the number of years driving (Maguire et. al., 2006). While it could be argued that cabbies had more brain volume than bus drivers before they started driving, the exacerbation of these affects as time went on argues against this theory.

This change in hippocampal volume is clear evidence of macroscopic structural plasticity in the brain. The taxi drivers in London are the elite performers in this situation. They ingest and synthesize incredible amounts of information on a daily basis. This study points to the fact that the amount and usage of this information is what contributes to the structural changes observed between the two groups. The taxi and bus drivers experienced similar amounts of stress while driving on busy London streets and both performed the physical task of driving all day. The main difference between the two groups is that the bus drivers drove a constrained route, while the cabbies constantly had to integrate their memorized information with the demands of their customers’ desired trips. This strongly indicates that the learning and spatial task of designing unique routes through London was the reason for the observed changes (Maguire et. al., 2006).

Although the cab drivers experienced these changes to their brain that made them well suited for their job, cabbies performed worse than the bus drivers when tasked with acquiring new visuospatial information (Maguire et. al., 2006). This suggests two things. First, there is a mental cost of altering the brain while mastering specific tasks. Second, neuroplasticity updates the brain to allow an individual to perform a specific task, but not every task, more efficiently.

Navy Sea, Air, and Land forces (SEALs) are a group of elite fighters who are highly trained and primed for combat missions in the harshest environments. Their training intentionally confuses them, deprives them of sleep, and subjects them to exceptional amounts of stress. These conditions, stretched over a training period of twenty-four weeks resets the activity levels in SEALs’ brains in response to stimuli like fear.

In 2012, Simmons et. al. took ten Navy SEALs and 11 age-matched healthy male volunteers and performed an anxiety activation task in an MRI scanner. The subjects of the study were shown either an image to relax them (positive image) or a combat image to induce stress (negative image). They were then instructed to press a button corresponding to whether a circle or a square was shown to them. The brain activity in response to the task was measured by fMRI. While the basics of structural MRI have previously been explained, fMRI can measure time dependent activation changes in a subject. Oxygen usage can be measured in the brain by measuring how much deoxy-hemoglobin is present in specific regions. Since only deoxy-hemoglobin, and not oxygenated hemoglobin, is paramagnetic, it is measurable by fMRI. The uptick in the signal from deoxy-hemoglobin means that oxygen is being used in that region of the brain. This measurement can yield the cerebral metabolic rate of oxygen consumption. If the cerebral metabolic rate of oxygen consumption is taken in conjunction with the change in cerebral blood flow and cerebral blood volume, the blood-oxygenation level dependent (BOLD) response can be measured. This gives a measure of real time activation in the brain. The T2* measurement pattern in fMRI detects small inhomogeneities in the relaxation of the sample after excitation, which makes it ideally suited for the measurements necessary to record the BOLD response.

Simmons et. al. found that SEALs modulated their brain activity depending on the stimuli provided. If a SEAL was shown a positive image, their brain activity in the insula region was higher than the control group. However, if the SEALs were shown a negative image, their brain showed significantly lower levels of activation than the control group in the insula region of the brain which is responsible for the reaction to the situation.

This decreased level of activation, when prepared for a negative stimulus and increased activation in the insula region of the brain when experiencing a positive stimulus, is evidence of neural tuning in Navy SEALs (Simmons et. al., 2012). Neural tuning is the idea that elite performers have adapted their brain to be prepared for a situation by responding in the most energy efficient manner. In this study, the SEALs were uniquely ready to respond quickly to a threat, and conserve energy when there was none. Since the insula is proximal to the vagus nerve which has parasympathetic effects if activated, the decreased activation would lead to an increased heart rate, more energy usage, and better reaction to a threat (Simmons et. al., 2012 & Breit et. al., 2018). This tuning of the neural response is a form of functional plasticity because there was not necessarily evidence of structural changes in the brain, but there is evidence of physiological tuning of firing rates due to training. Elite athletes regularly undertake mentally and physically strenuous tasks. Distance athletes are subject to physical and mental stresses for extended periods of time on a regular basis due to their necessary training schedule. A 2015 study by Ludyga et. al. examined eleven female and 18 male bicyclists using EEG. They found that the elite performers – those who had the highest maximal oxygen consumption (VO2MAX) – had structural and functional changes to their brain which worked in harmony to produce higher performance. It is important to note that VO2MAX refers to their ability to consume more oxygen if the situation requires it, not that they consume more oxygen when performing the same task as a non-elite athlete.

EEG is a noninvasive method to image the firing of action potentials, which are the basis for information transmission in the brain and to the body. An array of electrodes is placed on the surface of the scalp to measure the electrical potential generated by the ion currents caused by the firing of action potentials. While the temporal resolution is high in EEG, the spatial resolution of this method is lacking because potentials from distant sources can also be recorded by the electrodes. Another potential pitfall of EEG is a motion artifact, generated by rubbing the electrode against something else. Both of these are sources of noise in the measurement. The former is a limitation of the imaging technique. The latter was reduced in this study by recruiting experienced cyclists, who kept their upper body stable while pedaling (Ludyga et. al., 2016). This study found that the elite cyclists, those with a higher VO2MAX, had a lower level of arousal in the brain than an ordinary cyclist when generating the same power output (Ludyga et. al., 2016). This was noticed particularly in the central region of the brain which is the location of sensorimotor information integration for the lower extremities of the body. The precise location in the central region of the brain, however, cannot be determined by EEG due to its low spatial resolution. This represents a gap in the current literature. Further studies integrating methods like fMRI to measure the BOLD response are necessary to answer this question.

The EEG recording can be broken down into frequency components using the Fourier Transform. This yields useful parameters like alpha and beta power which correlate to neurons in non-operative modes during activation of other neurons in the brain and neurons at rest respectively. Alpha power is an inverse indicator of mental arousal and higher cognitive performance (Klimesch, 1999). Ludyga et. al. found that the elite athletes had similar changes in the ratio of alpha to beta powers, but that their baselines were different. The elite athletes used less total energy by selectively activating only the neurons needed for the task. This is because elite athletes’ brains are better at switching off neurons that are not being used for a specific task (Ludyga et. al., 2016). This results in higher neural efficiency and this finding, in conjunction with other studies, suggests this is caused by both functional and structural neuroplasticity.

Animal studies suggest that improved processing results from higher levels of integration of the cerebellar-thalamic-cortical circuit (Holschneider et. al., 2007). The increased levels of VO2MAX in the elite performers also suggest that there is an increase in vasculature in specific regions of the brain to supply more blood to only the necessary neurons. Neuroplasticity is influenced by the training, but also by the simple physical demands of needing more oxygen during extreme and extended exertion. This is evidence of how structural and functional plasticity work symbiotically to increase neural efficiency in elite performers.

This phenomenon is not unique to cyclists. Elite pistol shooters also showed decreased total levels of activation, but more efficient activation of neurons necessary for the task. Interestingly, there was even a significant difference in activation between good shots and bad shots in the elite pistol shooter group (Percio et. al., 2011). Elite performers, whether it be in driving a taxi-cab, combat, or athletics, experience modifications to brought on by training to perform their desired task at the highest level. These changes may be structural, like the increased size of the posterior hippocampus in London cabbies. They can also be functional, like the altered neural firing rates of Navy SEALs. The changes can be a combination of the two, exemplified by cyclist changing the level of blood flow reaching regions of the brain important to a task, and the specificity of activated neurons.

Each of these discoveries was made possible by using different neuroimaging techniques. MRI gives structural images of the brain. Functional MRI can be used to analyze changes in brain activation. EEG can measure the neural firing rates directly.

These discoveries contribute to the existing and rapidly evolving body of knowledge about the causes, manifestations, and effects of neuroplasticity. The brain, which was once thought to be a fixed and immutable structure has been shown to be a constantly changing organ which adapts to an individual’s circumstances. While these changes may prime an individual for a certain task, it may come at a cost to other functions the brain may one day have to perform. So, while London cabbies, Navy SEALs, and elite athletes have very different jobs, their brains are all uniquely suited to optimally perform their respective tasks.

Cognitive Flexibility.

We basically have 2 types of brain cells. There are the actual neurons which are the basic functional units of our nervous system and through which information is passed along.

Now next to that there are the lesser-known glial cells who take on a supporting role. There are all types of them microglia, oligodendrocytes, Schwann Cells, and so on. These glial cells are essential to the correct functioning of our brain from insulation to the removal of dead cells, over blood flow regulation and much more.

Our brain just wouldn’t function normally without them. And yes, they also play their part in neuroplasticity. For example, with the myelination process but, yeah, we’ll talk more about that later when we discuss the formation of habits. For now, let’s get back to neurons.

Neurons are unique for many reasons. Their shape is unlike any other cell in our body. So, at one end we have dendrites that look a little like tree branches who received messages from other neurons. There’s the cell body with the DNA in its nucleus or center. And then we have the Axon that looks like some kind of tail which is covered with Myelin. So, the message gets through faster and more efficiently. And then at the end of the axon again something resembling tree branches.

Now when the information gets to the tip of an axon branch it jumps over to the dendrite branch of the next neuron and that connection between the dendrite tip and the axon tip is called the synapse. So, what is neuroplasticity and where does it happen.

Now strictly speaking I need to make a difference here between Neurogenesis, which is the creation of new neurons and neuroplasticity which is the creation of new connections.

Now neurogenesis will automatically lead to new connections if the new neuron survives and is put to good use. That’s why many people use the word neuroplasticity when in fact they’re talking about neurogenesis. But when it comes to the plasticity of the brain neurons can do much more than just be created and connect to each other.

Neuroplasticity is much larger than only neurogenesis. Take the dendrites for example neurons can form new dendritic branches and spines increasing the size of their dendritic tree or behold they can do the opposite. They can shrink as well. So when we learn or experience something new over minutes to hours, anew dendritic spine emerges looking for the tip of an axon branch nearby. Over the next weeks they form a functional synaps that stabilize the new information and the contrary happens as well. Dendritic spines retract, eliminating synapses as information and memory fades. And that’s not the only place where we see neuroplasticity. At the other end of the neuron there’s quite some action has all with axons that can sprout offshoots into new directions and bridge quite some distance with sometimes spectacular results. Take a blind person reading braille for example. Now, as with anybody there’s an activation of the tactile cortex. But what’s unique with that blind person is that their visual cortex also gets activated. They’re blind, remember. It’s not supposed to happen. Apparently axons offshoots have found their way to the visual cortex as well. But that’s really surprising is the sensory cortex and the visual cortex are quite far apart. There’s even a case where a woman who was blind by birth had a stroke in her visual cortex after which she was unable to read braille anymore. And the contrary is true as well. Deaf people learning sign language or growing axons into their auditory cortex. It’s as if the neurons know where there is some unused real estate within the brain and then the Axons just go there and squat it. Injuries to our nervous system can remap in a similar way. For the sake of argument let’s say a person had a stroke and some damage occurred to the part of the cortex that receives tactile information from the hand. Now the hand has no damage. Neither do the nerve cells in the hand. It’s within the brain that the connection got lost. But the hand is fine. It’s just not communicating anymore. So the person loses sensation in her hands. Well in the following months and years axons from these receptors can sprout off and find a new way to re-establish communication using a bypass through neighboring parts of the cortex. This would lead to a partial return of the sense of touch for the person who suffered a stroke. But this remapping happens also without an injury having to occur. Take musicians for example who have a larger auditory cortex than non-musicians or London cab drivers who know their city by heart and have a larger hippocampus. Or more precisely The back part of the hippocampus which plays a role in memory and spatial maps. Or spent three months learning how to juggle and there is an expansion of the part of the cortex dealing with visual processing of movement. In other words what we do, our experiences, bring on changes in the number and strength of Synapses, dendrite branches and axons. Everything we do, or stop doing, has an impact in our brain. It continuously changes, evolves, adapts to answer to our immediate challenges in our everyday life. It is our immediate environment and how we interact with it, that ends up shaping our brain. In other words the way we interact with our environment is the key to rewiring our brain.

Over the recent years, there has been more cases of Alzheimer’s disease (AD) being diagnosed (Teixeira, Pallas-Bazarra, Bolós, Terreros-Roncal, Ávila, & Llorens-Martín, 2018). The characteristics that make up AD are advanced cell death that can result in degeneration of particular brain regions (Teixeira et al., 2018). This can result in deficits that include memory loss and loss in cognitive control (Teixeira et al., 2018). These characterizations that make up AD can highly decrease the quality of life (QOL) of the individual. Not only does this neurogenerative disease affect the QOL of the individual, it also affects the family. With AD, the individual may even forget their family members, or certain memories with them. Thus, highlighting how important finding ways to manage or treat AD can be. With the amount of people who are affected by this disease, it only warrants researchers like us to want to study ways to do so. One of these proposed ways is through the use of playing video games. With the rise of the video game industry, it has also resulted in a large negative aspect around them. Despite there being negative connotations surrounding video games, playing and using video games can results in an increase in our cognitive control functions.

Background Information

Video games have become a staple in many households, with countless hours and money spent towards this advancing industry. As this industry gains more traction with competitions, awards shows for the best of the best and the rise of esports being considered a possible sport, it opens up the possibilities of potential benefits. Recent studies have shown that playing video games improves aspects of cognition, such as attention and cognitive control (Mayas, Parmentier, Andres, & Ballesteros, 2014). An increase in alertness and reduction in distractibility was seen in the older adults who were in the test group (Mayas et al., 2014). One of the interesting aspects of their study was the affects that were resulted from their video game task, also transformed over to their performance in the oddball task (Mayas et al., 2014). Thus, suggesting some form of neuroplasticity had occurred in these individuals (Mayas et al., 2014). Although Mayas et al., (2014) had established correlation between video games and an increase in cognitive function, they were not the only ones to do so. Remarkable research conducted by Green, & Bavelier, (2006), examined the effects of action video games on visuospatial attention. There was on overall increase in visuospatial attention seen throughout all three experiments. Playing the action video games resulted in an overall increase in the amount of available attentional resources (Green, & Bavelier, 2006).

Other studies have examined how neuroplasticity can occur in certain individuals. The concept of neuroplasticity has been used in various clinical applications. Studies using methods of neuroplasticity have discovered ways to regain spinal cord function and brain function following injuries (Wolpaw, 2012).With these ideas in mind, it’s easy to think about how neuroplasticity can be used to regenerate brain functions that have been lost due to cognitive decline/disorders. This was the very idea that Fisher, Holland, Subramaniam, & Vinogradov, (2010), had. Fisher et al., (2010) conducted noteworthy research on the cognitive neuroplasticity that occurred in patients with schizophrenia. Participants had endured through cognitive training that increased the neuroplasticity in various regions of the brain such as memory and cognitive control (Fisher et al., 2010). The effects that resulted from this study were seen in the patients six months after the initial training had occurred (Fisher et al., 2010).

Another research study that found evidence of neuroplasticity in individuals with a disorder was Han, Chapman, & Krawczyk, (2018). This study focused on individual who had suffered through a traumatic brain injury (TBI). Through the use of cognitive training, the results of this study indicated changes in the neuronal networks on connectivity in the induvial with TBI (Han et al., 2018). Other results from this study provided evidence of neuroplasticity occurring in these patients with chronic TBI (Han et al., 2018). On the contrary, a study conducted by Kumar et al., (2017) discovered impaired neuroplasticity occurring in the prefrontal cortex of individuals with AD. They believed these results could show the relationship between impaired prefrontal cortex neuroplasticity and its affect in working memory for those with AD.

While these previous studies have shown extensive research on the effects of video games and neuroplasticity, Gong et al., (2017) research is another notable study. Gong et al., (2017) examined working memory networks in correlation with action video games. Action video games experience was found to increase working memory networks in the prefrontal cortex (Gong et al., 2017). Since there was an increase in the prefrontal cortex, Gong et al., (2017) established a correlation between working memory neuroplasticity and video games. This suggested that playing action video games could have a clinical basis.

From these previous research studies, it is clear that the effects of videos can cause an increase in cognitive control. As well they have demonstrated the effects of neuroplasticity in certain populations of individuals. Some of the studies have found a link between neuroplasticity cognitive control and video games, however none of the studies focused on individuals with AD. The current research focuses on comparing how the impact of playing video games can cause an increase in cognitive function through neuroplasticity. This study seeks out to prove the possibility of neuroplasticity occurring in individuals with neurodegenerative diseases. The literature that was described consisted of many different studies that touched on various individuals of different populations, such as older adults or individuals with schizophrenia. This study will combine the effect of playing video games with participants with AD. This current study will utilize a conditioned video game training group alongside a control group and with the analysis of functional magnetic resonance imaging (fMRI) scans and cognitive data to do so. We hypothesis that the conditioned video game training group (test group) will show an increase in their neuronal activity in the prefrontal cortex in the fMRI scans from their first scan to their second scan. As well the conditioned video game training group will still show an increase in neuronal activity from baseline in their final scan three months later. Lastly, we hypothesize that the video game training group will perform better in the cognitive control video game test.

Method

The variables to be manipulated in the study will be the training the two different groups go through. The control group will not be going through a conditioned video game training program, rather they will be exposed to various video games that are readily available. The test group will be going through a conditioned video game training that will follow a strict regimen. Both groups will be tested at the end on a specific video game that is to test their cognitive control.

The variables to be measured from these tests are the levels of brain activation obtained by brain imaging scans (fMRI), at three different times. In addition to this, the level of success that will occur during the final video game will also be monitored. This will measure the level of their functional cognitive control through the various sections of the game that will occur, such as decision making and working memory. As well, the video game will serve as the cognitive task

Participants

Older adults that are diagnosed with AD and are above the age of 60 will be included in this study. The ~50 participants will be recruited through a mental health treatment center in the community and all participation will be voluntary. Participants will have to give a written consent whether through them or their guardian to be able to participate in the study. Participants of a variety of different cultural backgrounds and different genders will be accepted into the study. Approximately Twenty-five of the participants will belong to the control and the other approximate twenty-five will belong to the manipulation group. The group that will be assigned to the participants will drawn by random assignment to eliminate interviewer bias.

Procedure

As soon as the participants are initiated into the study, they will undergo a fMRI scan to obtain a baseline activity levels of their brains. For the study, participants will be using software that has been developed previously by a company (Fisher et al., 2010). This software contains various video games that have been developed to engage certain aspects of cognitive control (Fisher et al., 2010). Participants will be randomly assigned to either the control or test group. This will assign them a log in for the computer, depending on which group they are in, the tests will appear for that. For the control group, the various commonly used video games will be accessible and for the test group the controlled video game training will be available. Participants will attend a weekly one-hour session for ten weeks. During this time the control condition will continue to use the computer to play whichever games they have access to. The test group will progress through the training course one week at a time. After ten weeks of training have occurred, each participant will be coming back the following week to participate in the final video game test. The test will be calibrated so that is hits certain features of cognitive control such as working memory, and decision making, through the various quests that will need to be performed. This test will be graded out of a score of five. After the test the participants will undergo another fMRI test. From the date that they had their video game test, participants will be brought back three months to undergo a third fMRI scan.

The study will be conducted after being approved by the ethics board of the university. The participants will be informed what they would be taking part in a study that would examine their cognitive control. The true reason for the study will be hidden from them through the manipulation of the hypothesis. The experiment will be taking place in one of the labs in the university. After each participant has gone through the whole study, the participants or their guardians will be debriefed about the study and will be told what the hypothesis really is. At this moment if any participants feel they are being misled, they will be able to withdraw their data from the study.

Predicted Findings

Going off of the interpretation that our hypothesis was correct, the results of the study should be as following. The pattern of data to be expected in the fMRI scan analysis is that in the control group there should be no difference in the amount of neural activation throughout the three scans. As well the data that will be collected from the cognitive control video game test, which will be analysed through the use of ANOVA, should remain at baseline levels. Predicting that the mean for the control group would remain under fifty percent. For the test group, the fMRI scan data analysis should increase from each scan that is conducted. In the second scan there should be an increase in neuronal activity in the prefrontal cortex. In the third scan the neuronal activity will resemble the same as the second scan. As for the cognitive control video game test, the results for the test group will indicated an increase in working memory and cognitive control. Predicting that the results for the test group will be above fifty percent.

Interpretations

The implications that can be drawn out from the results that are targeted towards neuroplasticity is that neuroplasticity still has the ability to occur in brains that have degenerated due to various reasons. Thus, this provides a gateway to treatments that can help those with neurodegenerative disorders. This can increase the QOL of these individuals as neurodegenerative disorders can be life deliberating. For further implications in the field of neuroscience, these results indicate further results of the effects of neuroplasticity. As well, the results provide further information on understanding how the brain adapts to abnormities towards it. In the interest of humans, these results prompt hope that there can be improvements or possible cures for those with neurodegenerative diseases. As of right now, the QOL can degrade very quickly with those with neurogenerative disease. This does not only affect the individuals diagnosed but the family as well. With advances such as this study, the QOL of these individuals and their families can be improved. Further research that can be done to follow up on the findings of these study can be replications of the study. With replications of the same study, with the other study producing similar results, the results of this study will be more concrete. Further research can be done in this field with other neurodegenerative diseases. As well, further research with neuroplasticity can examine what affects would occur through earlier interventions. The greater the research that is conducted in this field, the one step closer we will be for finding possible cures.

Neuroplasticity can be defined as brain’s ability to change, remodel and reorganize for purpose of better ability to adapt to new situations. Neural networks are not fixed, but occurring and disappearing dynamically throughout our whole life, depending on experiences. While we repeatedly practice one activity such as a sequence of movements or a mathematical problem, neuronal circuits are being formed, leading to better ability to perform the practiced task with less waste of energy. Once we stop practicing a certain activity, the brain will redirect these neuronal circuits by a much known ‘use it or lose it’ principle. Neuroplasticity leads to many different occurrences, such as habituation, sensitization to a certain position, medication tolerance, even recovery following brain injury. Neuroplasticity also occurs hand-in-hand with synaptic pruning, which is the brain’s way of deleting the neural connections that are no longer necessary or useful and strengthening the necessary ones. How your brain decides which connections to prune out depends on your life experiences and how recently connections have been used. In much the same way, neurons that grow weak from underuse die off through the process of apoptosis. Apoptosis is defined as the death of cells which occurs as a normal and controlled part of an organism’s growth or development. Two well-known research studies into neuroplasticity were conducted by Maguire et al. (2000) and Rosenzweig & Bennet (1972).

Maguire et al (2000) examined the role of extensive navigational experience on the shape and size of the hippocampus. The study conducted was a qausi-experiment using a single blind method where the researches did not know which group the brains the were measuring came from. The sampling method was through volunteering and from those volunteers 16 right-handed male taxi drivers who passed the knowledge test to become a full driver were selected, with the target population being those with extensive navigational experience. Taxi drivers were selected as they were theorised to have extensive navigational experience. 50 right-handed males were used as a control group. MRI’s were used to measure the brains using VBM for a measure of density and pixels for size of the hippocampi. Researchers found that the posterior hippocampi were larger in the taxi drivers while the anterior hippocampi were larger in the control group. There was also a positive correlation with years’ experience and density of the hippocampus. As there was a difference in the size of the hippocampus between the two groups, it can be concluded that the experience of the taxi drivers directly caused the changes in their hippocampi.

Although the research was limited by sampling considerations, it was well controlled giving it good internal validity. A small sample limits external validity because the results most likely will not be normally distributed and thus cannot represent the target population. The strengths of the research are that both the variables and bias were well controlled. The variable of interest was control by the research through the use of the Knowledge Test. As the sample was exclusively male and right-handed, the control participants were also controlled for these two variables. Likewise, the use of the single blind research design meant that researcher bias was controlled. On the other hand, although researcher bias was well controlled, there are some limitations of the research in regard to gender and culture representations. The sample was exclusively male and right-handed and therefore cannot be generalised without caution to female and/or left-handed individuals. In addition, as the sample was collected solely from London taxi drivers, some caution needs to be used when generalising outside of the sample. The research design was a quasi/natural experiment as the independent variable, navigational experience, could not be manipulated. Therefore, it can be assumed that extensive navigational experience would be found in individuals with who have to ‘navigate’ as a part of their everyday life. Therefore, with the limitations of the sample noted above taken into consideration, the sample can be considered to represent the target population. Although replication of the study with a more balanced sample would increase the validity of the research in support of the theory, all in all, the research carried out by Maguire et al. provides credible evidence in support of the theory of neuroplasticity.

A study that investigates the effects of a deprived or an enriched environment on neuroplasticity is an experiment conducted by Rosenzweig & Bennet (1972). The aim of the study was to investigate whether environmental factors such as a rich or an impoverished environment would affect the development of neurons in the cerebral cortex. In the experiment, male rats were chosen from different litters to be randomly allocated to three different conditions: In the control condition (CC) there were three rats in the cage. In the impoverished condition (IC), the researchers placed each rat in individual cages. The individual cages lacked the toys and the maze which were in the enriched environment. For the enriched condition (EC), the researchers placed 10 – 12 rats in a cage containing different stimulus objects to explore and play with. All groups had free and adequate access to food and water. The rats were kept in these condition for 30-60 days before being killed to study changes in the brain’s anatomy. The scientist conducting the autopsy and studying the brain did not know what condition the rat came from as to assist with validity. The rats in the enriched environment had a heavier frontal lobe and thicker cortex compared to the rats in the deprived environment. The researchers also noted that rats in the EC condition had developed significantly greater activity in the neurons in the cerebral cortex associated with transmission of acetylcholine. This may have resulted from the exposure to the toys in the stimulating environment, which helped to develop neural connections in the rat’s brain.

Since rats and humans are similar, brain-wise, the implications of the study are that the human brain should also be affected by environmental factors such as intellectual and social stimulation. It is now known that poverty is a major risk factor in children’s cognitive development as poverty is related to a number of risk factors such as poor nutrition, lack of access to good education and poor health. As Rosenzweig used rats for the experiment, it is difficult to generalise the findings to humans. There is also an ethical consideration on the cause of undue harm and stress onto the rats during the study. However, as it was a single blind study, and that there were numerous follow-up studies, the experiment has overall good validity. Rosenzweig’s experiments have had a significant impact on psychology as they clearly show that there is a cause and effect between the environment and brain development.

Neuroplasticity is the brain’s ability to reorganize itself by forming new neural connections throughout life. Neuroplasticity allows the neurons in the brain to compensate for injury and disease and to adjust their activities in response to new situations or to changes in their environment. There are also limits to neuroplasticity being that its limited, but the strengths outweigh its weakness allowing the brain to retain much more important knowledge for longer. Neuroplasticity is a credible because it effectively explains behaviour and brain structure and has a number of applications. Within the theory itself, however, further research is required to uncover its aspects that are still unclear and to overcome its limitations.

Introduction

How Does our Brain Change? I am submitting this for class Psych 6014 A Biopsychosocial Approach to Counseling. The Program for this presentation will be as follows: I will start with a brief overview of Brain development focusing on the important aspects for Brain Plasticity followed by a description of Brain Plasticity, the history of Neuroplasticity, the fundamentals and why it is so important. I will then give a brief story of neuroplasticity from the work of Dr. Barry Sternman on Neurofeedback and its effects on temporal lobe seizures Finally, I will discuss Brain Plasticity and its implications for Psychotherapy.

Brain Development: Anatomy of the Brain

The anatomical stages of brain development begin early on in the prenatal months. The brain’s structure is predetermined before birth by our genetic makeup. However, there are many other elements that can impact that development, both prenatally and postnatally. An example of pre-natal toxins on brain development are maternal smoking and/or drinking. Smoking has been found to lead to possible changes such as reduced brain growth, altered brain microstructure and changes in brain function (Ekblad et. Al, 2014). Perinatal changes in the brain structure can be caused by physiological elements such as nutrition and toxins, and psychological elements such as attachment. In the following insert, one can see what elements in maternal smoking result in these changes and the mediating factors that lead to them. (Ekblad et al, 2016, p. 13) The first stage of brain development is neurulation. Within three weeks after conception, the embryo has developed into a three-layered spherical formation. The cells begin to thicken and form into what is referred to as the neural plate. This plate continues to fold over on itself, creating a tube that will eventually close at the bottom and top. This structure, called the neural tube will continue to develop into the central nervous system (CNS), which consists of the brain and spinal cord. The outer cells of this structure are referred to as the autonomic nervous system which is made up of the nerves that lie outside the brain and spinal cord and are referred to as the peripheral nervous system (PNS). As the brain continues to develop it will section off into four main structures: The Brainstem, which is what connects the brain and the spinal cord and is responsible for basic life functions such as breathing, heart rate and our bodies natural rhythms; the Diencephalon contains the thalamus and the hypothalamus, which act as a relay station between the cerebral cortex and subcortical areas of the brain; the Cerebellum, is responsible for motor control, balance, equilibrium and muscle tone and is located just above the brain stem at the back of our head; and lastly the Cerebrum, which consists of the Cerebral Cortex and a number of other subcortical structures. The Cerebrum is the upper part of the brain and controls conscious mental processes. The outer layer of the cerebrum is called gray matter, the inner portion, white matter. It is arranged into two hemispheres called cerebral hemispheres. The area that separates the two hemispheres is called the Corpus Collosum, which is a large thick nerve tract that connects the two hemispheres and sends messages back and forth. The cerebral hemispheres are divided into four sections or lobes: the frontal lobe, responsible for thinking, making judgments, planning, decision-making and conscious emotions, the Parietal Lobe, mainly associated with spatial computation, body orientation and attention, the Temporal Lobe, concerned with hearing, language and memory, and the Occipital Lobe, mainly dedicated to visual processing. The following picture demonstrates the lobes of the brain and their functions. https://psychotherapycanada.com/neuroplasticity Alliance Psychotherapy Axons, Dendrites & Synapses The brain is made up of about 86 – 100 billion neurons. It is important to note that these neurons differ from other cells mainly because they have a cell element called dendrites and axons. The dendrites bring electrical signals to the cell body and the axon takes information away from it through an electrochemical process. Our neurons carry messages in the form of electrical signals which are called nerve impulses. To create this impulse the neuron needs to be aroused, perhaps by a thought or an experience in order to send a current through the cell, which either excites or inhibits the neurotransmitters at the end of the axon. Data will transfer from one neuron to another neuron via a synapse or a gap. The synapse is the small space between the two neurons. At birth, every neuron has around 2,500 synapses and by age three, this number has grown to close to 15,000 synapses per neuron. However, most adults will only have half of this number because as we age and experience new events, some connections are strengthened while others are eliminated. This process is referred to as synaptic pruning. The neurons that are used more often strengthen their connection while those that are rarely used will eventually die. This was first described by Donald Hebb who in 1949 showed that “any two cells or systems of cells that are repeatedly active at the same time will tend to become ‘associated’, so that activity in one facilitates activity in the other” (Hebb, 1949, 70). In simpler terms it is often referred to by the adage “What fires together, wires together” and it is through this process the brain is able to adapt to its ever-changing environment – now known as Brain Plasticity.

Brain Plasticity History

Although today we are well aware that the development of the brain is a lifelong process, it was not until the late 1800’s that the term plasticity was first heard in any reference to the brain. It was William James that suggested that the brain was not as unchanging as previously believed and in his book The Principles of Psychology (1890), he wrote that “organic matter, especially nervous tissue, seems endowed with a very extraordinary degree of plasticity (James, 1890)”. Unfortunately, this theory was ignored for many years until the 1920’s when Karl Lashley studied rhesus monkeys and demonstrated that there were changes in neural pathways. At around the same time, Santiago Ramon Cajal, also known as the father of neuroscience coined the phrase “neuronal plasticity” to describe nonpathological changes in the structure of adult brains. He acknowledged that the brain was able to change even during adulthood and did not stop throughout the lifespan. But it was not until the 1960’s that researchers began to discover that neurons were capable of recovery after a traumatic event and thus were even more malleable than previously believed. With time and research, it has been determined that the brain has the remarkable capacity to reorganize pathways, create new connections and even create new neurons, known as neurogenesis. What is Neuroplasticity The brain is a very complicated tool and although as was pointed out previously, until the last century it was considered to be a static organ that stopped developing in early adulthood. We now know that this perception is false and that, in fact, the brain is continuously changing and developing and this is due to the nature of its own plasticity. One may think of the term plasticity as an odd way to refer to our brain and may possibly make you think of plastic cups or your child’s Barbie doll; however, it is a very common term when referring to the brains ability to be malleable (as some plastics are) throughout the life span. This neuroplasticity is best described as the brain’s ability to not only change but to re-wire itself as a result of experience and/or trauma. The brain goes through these changes in order to develop and adapt not only to new experiences and environments but also to optimize healing after any type of brain injury.

There are two types of Neuroplasticity:

• Structural – This is the change that happens when we create new synaptic connections and add new neurons.
• Functional – this is the brain’s ability to move functions of the brain from a damaged area to an undamaged area.

An example of this are the many studies that have shown superior hearing and olfactory senses in people that are born or even become blind (Areneda et.al, 2016). This happens because the two enhanced senses have now taken up neurons and space given up from the occipital lobe. It is important to remember that plasticity can also be additive or subtractive. As Norman Doidge points out “Additive plasticity occurs when the brain change involves growth. But plasticity is also subtractive and can involve taking things away as occurs when the adolescent brain prunes away neurons, and when neuronal connections not being used are lost” (Doidge, 2007, p 298). How does it work: Although there are already synaptic connections made by the time the infant comes into the world, the real work begins then. Picture a large set of building blocks with a billion tiny pieces. The possibilities are infinite but it will take a very long time to assemble them. Dr. Merzenich,(2013) also referred to as a father of neuroplasticity, describes the baby’s brain in the following way: “You can imagine a newborn’s brain like a highway map of North America or Europe or Asia with just the largest freeways and most important highways laid onto the map. Those major thruways interconnect regions to one another — but no one has yet constructed any local highways, secondary roads, streets, byways, lanes, driveways, or garden paths. Most places (specific abilities) remain inaccessible until these routes are in place!” (Merzenich, 2013, p. 39) As mentioned, the brain is made up of billions of neurons, and each neuron is connected to thousands of other neurons through its dendrites – tree like branches that carry signals from one neuron to the next. Whenever you learn something new, your neurons form new connections with other neurons, and a new pathway in the brain is established. Dendritic branching is the process by which the dendrites of one neuron branch out to establish connections with other neurons. The sum total of all your brain’s neurons, and the connections between them, can be thought of as an enormous neural network. Every thought, memory, emotion or behavior is linked to a certain neural pathway in the brain. The more often you engage in a certain neural pathway, the stronger that pathway becomes, and the more likely it will become activated in the future. That is how habits form (which can be both a positive and a negative aspect of brain plasticity). On the other hand, when we stop using a pathway – for instance, give up practicing a musical instrument that pathway will weaken and, in some instances, disappear. The interesting aspect of brain plasticity is that our brain changes with every new thing that we do. An example of this is that if you read your child a bedtime story, you change the child’s brain but you also change your own brain. There is a real simplicity in what can actually change our brains. Children begin by having no control over how their brain changes, which is why events and experiences, such as learning and attachment can have such a lasting effect. This makes the nervous system particularly vulnerable during the developmental stages and David Wallin in his book on Attachment and Psychotherapy (2007) states, “Healthy relationships of attachment, especially in the first years of life are necessary for the development and integration of right and left brain functions – and of limbic and cortical functions as well” (Wallin, 2007, p. 78) As we age, we begin to learn how to control our selective attention and in turn we gradually learn to control brain change. As children grow into adolescence and adulthood, the brain starts to only allow change to take place when it chooses. But a key point to remember is that brain activity is crucial for brain reorganization; stimulating our brains through environmental stimuli is a requirement for creating new and strengthened synaptic connections. It is now evident that our biological makeup is only one factor in determining how our brain will evolve. Our environment and will always play a vital role in the shaping and reorganization of our brains; changes in neural pathways result from various types of experiences – both positive and negative.

Positive and Negative Effects of Neuroplasticity

Although our brain is an extraordinary organ that is incredibly capable of adapting to its environment, it is also neutral in nature. It does not know the difference between positive and negative. It will learn whatever is constantly repeated, which can result in behaviors that are either adaptive or maladaptive. So, in this way, neuroplasticity is not always working in our favor and just as athletes rewire their brains with practice, so do many negative behaviors such as self-criticism, drug and alcohol abuse, gambling to name a few often lead to mental disorders such as depression, anxiety, obsessiveness, drug dependency and over-reactive tendencies. But positive brain plasticity results in beneficial behavior outcomes. An example of this would be by improving the neural networks responsible for cognitive functions such attention, memory and mood. There are many ways that we can go about improving our brain function, one example of this is mindfulness. Individuals who continually practice meditation learn to control their attention and eliminate distractive thoughts. Repetitive practice of mindfulness encourages structural growth of synaptic linkages among activated neurons. These networks in the prefrontal cortex are strengthened and lead to physical changes such as improvements of the immune system, lower cortisol levels and blood pressure. Another great example demonstrating the benefits of brain plasticity are the changes observed in individuals who attempt to learn a new skill. A study involving music training found that by measuring magnetoencephalography results of individuals with an average age of 26, there was a noticeable difference in the prefrontal cortex and noted that there was a greater neuroplasticity response in musicians who had long time training than those that practiced less. In a similar study observing individuals who were between the ages of 60-84, after 4 months of piano lessons there was a significant improvement in their mood, wellbeing, cognitive function, attention, motor and visual function and executive functioning (Shaffer J. (2016) ). It is important to note here that Brain Plasticity can have negative effects and most of us have some habit we wish we could break and now have an understanding of what we need to do to prune those synaptic connections and replace them with more positive connections, which through effort and practice we can strengthen to become our new norm. Following is a short story about how Neurofeedback, which is a brain therapy that relies not only on operant conditioning but on the knowledge that the brain can change has made a difference in the world of neurology because of its effects on temporal lobe seizures.

Plasticity and Therapy

Neurofeedback & Temporal Lobe Seizures In 1967 Dr. Barry Sternman did research on cats trying and succeeding in changing their brain waves by the use of Neurofeedback and operational conditioning. After the publication of his article, he was approached by NASA because a number of their astronauts were experiencing seizures due to exposure to the toxic chemical Hydrazine. Dr. Sternman then began another experimentation exposing cats to Hydrazine to see what neurological effects they would experience. The cats demonstrated seizures and other neurological effects except for a small number that appeared to have a very high tolerance and did not exhibit seizure activity. These were the same cats that had been in the previous Neurofeedback experimentation. The results of this was that the cats that had gone through NFB and had changed their brain waves had also changed the physiological structure of their brains. This new knowledge resulted into investigations on the value of NFB and seizure activity. NFB has been found to be efficacious in the treatment of temporal lobe seizures in humans by either reducing the number of seizures as well as in some cases eliminating them altogether. This is a perfect example of how brain plasticity can serve to heal the brain by altering its very structure. Psychotherapy Prior to neuroplasticity becoming a major area of research, all mental disorders were considered exactly that – a mental disorder. There was a saying that psychiatrists are the only physicians that do not look at the organ that they treat. This is no longer true because the fields of psychiatry and psychology are starting to recognize brain therapies: EMDR, Brain Spotting and Neurofeedback. These are therapies that are utilized in helping clients to deal with their mental pain and anguish. If we accept that adults are capable of directing their neuroplastic changes via attention and practice of new behaviors, then through the help of psychotherapy they can do exactly that – direct their attention, change behaviors and learn new ways of thinking that will slowly prune the connections that have strengthened their disorder and strengthen the connections that are now new and more effective for healthy living. Just like an exercise therapist or physiotherapist can create new synaptic connections and force other areas of the brain to take over when there has been an injurious loss, so too can psychotherapy change the brain to heal psychological trauma and pain.

Conclusion

In reading about brain plasticity and learning about how our thoughts and behaviors are linked to the strength or the weakness of our synaptic connections, it has strengthened my resolve that when working with people who come to us for help on any level, we must take a biopsychosocial approach. If our psychological perspectives and our social support systems have an effect on our very brain structure, counsellors must address the biological effect on the brain as we try to help our clients change behaviors, reframe thoughts and start changing behaviors to be more adaptive. I am left with the question “Are mental disorders not brain disorders?”