SEPTEMBER 2018 Vol

The Journal of the IYNA

SEPTEMBER 2018 Vol. 2 Issue 5

Featured Articles

‘Brain Versus Com- ‘The Brain of a puter: A Comparison Honeybee’ of Structure, Meth- - Vilena Lee ods, and Capabilities’ - Khayla Black

International Youth Neuroscience Association

–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Contents INTRODUCTION Letter from the Editors IYNA Editorial Team page 2

GENERAL NEUROSCIENCE The Brain of a Honeybee Vilena Lee pages 3-7

The Neuroscience Behind Imagination, Kimaya Gadre pages 8-10 or What We Imagine it to be

Neurolinguistics: The Intersection of Language Geetanjali Rastogi pages 11-14 and the Brain

DISEASE Protein Dysregulation in Amyotrophic Lateral Sarah Shirley p ages 15-17 Sclerosis

RESEARCH Oxytocin and Social Cognitive Decits Tobey Le pages 18-20

NEUROTECHNOLOGY Brain versus Computer: A Comparison of Khayla Black pages 21-26 Structure, Methods, and Capabilities

INTERVIEW An Interview With Elisabeth Glowatzki: Dharshan Varia pages 27-30 Departments of Otolaryngology and Head and Neck Surgery and Neuroscience at Johns Hopkins University

Zebrash and Hearing: An Interview with Dr. Chinmayi Balusu pages 31-35 Allison Con

CONTRIBUTORS PAGE page 36

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・I NTRODUCTION・ –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Letter From the Editors Sojas Wagle, Robert Morgan, Anita Singh, and Miruna-Elena Vlad

Dear Readers,

Welcome to the fth issue of the second season of the IYNA Journal! We greatly appreciate your readership, continued or new. This is the second issue with our redesigned journal process where we now have a rolling basis for article publications. This means that every article that is submitted before the deadline will not necessarily be published for that specic issue, but publication in a future issue is virtually guaranteed if the author makes changes to their article as directed by the editors’ suggestions. We are pleased to announce that it has been going very smoothly, and we will be continuing with it in the future. Recently, we’ve also decided to disband the assembly team of the IYNA Journal and instead to expand the role of editors to include formatting capabilities. We hope this will boost the morale of our editing team by making their tasks more dynamic, and we also hope our authors will receive more of the optimal care and attention they need to succeed as writers. That being said, here are some previews of articles in this release: In the General Neuroscience section, Vilena Lee discusses the neurological mechanisms that allow the honeybee to have a cognitive ability comparable to mammals, Kimaya Gadre seeks to redene imagination by clarifying that the propagation of new ideas stems from previously learned concepts, and Geetanjali Rastogi reveals the neuroanatomy and research ndings behind the growing eld of neurolinguistics. In the Disease section, Sarah Shirley investigates the pathological mechanisms in which protein aggregation develops and causes Amyotrophic lateral Sclerosis. In the Research section, Tobey Le explains the correlation between the oxytocin hormone and an individual's ability to engage in a social environment. In the Neurotechnology section, Khayla Black highlights the dierences between the human brain and the modern computer and suggests that, in the future, they may cease to exist. Finally, in the Interview section, Dharshan Varia uncovers details about Dr. Elisabeth Glowatzki’s seminal research on the function of auditory nerve bers in the mammalian cochlea, while Chinmayi Balusu interviews Dr. Allison Con to nd out more about her groundbreaking research on how larval zebrash respond to loud noises or damaging drugs. We would like to recognize all of our dedicated editors for helping us make this issue the success that it is. You can see all of their names and positions on our Contributors page. If you have any questions, comments, or suggestions for us, please feel free to contact us at [email protected]. We hope you enjoy reading this issue as much as we enjoyed editing it!

Best Regards, Sojas Wagle - IYNA Journal Editor-In-Chief Anita Singh, Robert Morgan, Miruna-Elena Vlad - Senior Editors

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・GENERAL NEUROSCIENCE・ ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––

T he Brain of a Honeybee

Vilena Lee

Abstract

Honeybees dierentiate themselves from other insects due to their ability to practice advanced cognition. Scientists have determined this by studying honeybees’ process of “foraging”. Worker bees are able to communicate to other bees in the hive the distance and angle at which a food source is found. By being able to communicate the location of the food source, honeybees have proven to have advanced memory skills relative to other insects. Honeybees, unlike humans, do not have a hippocampus or a prefrontal cortex, so scientists believe that honeybees exhibit these higher cognitive functions through their Mushroom Bodies, which are bilateral anatomical structures that are packed with neurons.

General Overview

Honeybees, unlike other insects, are known for their high intellect and advanced cognitive ability. Honeybees have approximately 1 million neurons despite having a brain the size of a sesame seed [1]. This allows their brain to have a greater density relative to other insects and their nervous system to be complex for such a small size. It is because of this that scientists have begun to use honeybees to conduct research on the brain. Bees have demonstrated strong cognitive ability with advanced learning and memory skills. “Foraging,” which is the process when bees exit the hive to gather nectar, is a distinct trait of honeybees, where worker bees that are older than 21 days are sent out to collect food for the hive [2]. There are two types of worker bees who forage for the hive: scout bees, and reticent bees. Scout bees go outside the hive and search for the best food source. When they return to the hive, it is critical that scout bees communicate to reticent bees information on the food source through a dance.

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Communication Through Dance

After a scout bee evenly distributes nectar into honeycombs, she will acquire an audience [3]. With the attention of the audience, she will do one of two dances: either a round dance or a waggle dance. The dance that she decides to do will tell the bees the quality and quantity of the food source. If it’s a strong, rich food source, all of the foraging bees will dance with great enthusiasm each time they return to the hive. On the contrary, if the food source is weak, the dance will not be as vigorous.

A round dance is used for food sources that are fewer than 100 meters from the hive. The scout bee will distribute her newly acquired nectar to other bees in the hive and will then begin to “run” in small circles. She will switch directions every few minutes, and the dance will be repeated no more than 3 times. A waggle dance is for a more distant food source. Because the food source is farther away, it is more likely than not that the food source is stronger than a round dance food source. The “waggle” comes from the fact that the worker bee will dance in a gure-eight or sickle shaped pattern. The waggle dance tells the bees about the direction and energy required to reach the food source. The distance is given by how long it takes the bee to complete one “circuit” in 15 seconds. For example, if a bee completes 8-9 circuits in 15 seconds, the food source is approximately 200 meters away. However, if a bee completes 2 circuits in 15 seconds, it is estimated that the food source is about 2000 meters away. Direction is given to the hive by the direction of the dancer as she does her “waggle” dance. If the worker bee completes her “waggle” while upwardly facing the audience, then the hive can assume that the food source is facing towards the direction of the sun. On the other hand, if a worker bee does a “waggle”, and she completes the dance at 70 degrees upward to the left of the audience, then the hive will assume that the food source is 70 degrees to the left of the sun.

The Honeybee Brain

Honeybees are able to learn and make complex decisions that will benet their hive. According to research completed by Dr. Karl Von Frisch, it was disproven that honeybees are “hardwired” to be able to calculate distances and communicate the information to the hive. Individual bees are unable to program themselves to memorize locations, ower quality, and hive sites; they only live for 7 weeks during the summer time [4]. Rather, honeybees are able to complete such monumental tasks through their advanced observational learning. Honeybees are able to learn

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–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– taste, smell, and touch information through the process of foraging. With this information, bees are able to generalize sites for food sources beyond simpler categories [5]. This ability for bees to learn and adapt through what they’ve seen and encountered have caused scientists to hypothesize that bees are able to adjust to their environment through neuroplasticity just like humans [6]. Scientists have attempted to classify bees in behaviorist terms; however, bees are too complex to dene as a classical term, since they have the anatomical structure of insects, yet the cognitive ability of mammals.

Bees are also able to take time of day, location, and several dierent sensory stimuli into account when deciding to forage. This has allowed scientists to also hypothesize that bees are able to show integrated memory. Bees have demonstrated short-term memory (lasting a couple of days) as well as long-term memory (lasting their whole lifespan). In humans, the prefrontal cortex is the place for higher order cognition and reasoning ability. Bees, and insects as a whole, do not have anything that resemble a prefrontal cortex. Bees do, however, use epigenetic methods for memory [7]. For long-term memory, bees are believed to use DNA methylation.

DNA methylation is a molecular mechanism used to regulate memory specicity through the experiences and environments that an organism has accumulated over their lifetime [8]. These mutations occur in DNA and not within the DNA sequence. It is also possible for the mutations to be inherited. There is a hypothesis that DNA methylation correlates to the storage of memories through activating the transcription of genes that encode for proteins whose function is to regulate memory [9]. DNA methylation is believed to be a key mechanism for governing synaptic plasticity as well as long term storage in cortical regions of the brain [10]. This has led scientists to hypothesize that epigenetic regulation in cortical brain sites are able to be directed by memory-based plasticity within the hippocampus. Unfortunately, bees have nothing within their nervous system resembling a hippocampus either.

Mushroom Bodies

Mushroom Bodies (MBs) are an anatomical structure containing densely packed neurons [11]. MBs are comparable to the cortex and hippocampus of humans because these structures are what give honeybees their advanced cognition. They are found in the anterior regions of insect brains, most notably with ies and honeybees [12]. MBs are a center of associative learning and behavior (e.g. olfactory learning, habituation, temperature regulation, and sleep). MBs are constructed through –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 5

–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– major intrinsic neurons called Kenyon cells as well as 50 other types of extrinsic and intrinsic cells. Kenyon cells are critical for receiving olfactory projection neurons and other critical sensory inputs. Honeybees have a much larger and complex MB system than other insects or other bees for that matter. French biologist Felix Dujardin was credited with accumulating a large body of evidence that demonstrated the idea of MBs being a multisensory brain region critical for the formation, storage, and retrieval of associative memories [13].

Signs of neuroplasticity have been demonstrated within the MBs of honeybees. T he mushroom body is believed to act as a combination of the human hippocampus and sensory cortex. This advanced neurological integration of signals develops into memories over time, increasing the honeybee’s ability to navigate in dierent situations. The MBs of honeybees have been proven to exhibit structural plasticity during adult behavioral development. However, neurogenesis is a rare occurrence in honeybees of all ages. Therefore, scientists believe that while honeybees are able to rewire their existing neurons to allow them to adapt to learning and memory, they are not, or typically not, capable of birthing and proliferating new neurons [14]. Because honeybees are able to adapt their currently existing neurons as a response to stimuli, yet are not able to generate new neurons, scientists prefer to claim that honeybees exhibit synaptic plasticity rather than neuroplasticity.

–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– References

{1} Frisch, Karl von. (03/09/2014). “Dance Language of the [8] “DNA Methylation.” W hat Is Epigenetics?. Honey Bee.” E xtension. www.whatisepigenetics.com/dna-methylation/. Retrieved; articles.extension.org/pages/26930/dance-language-of-the- 16/05/18. honey-bee. Retrieved; 10/05/18.

[2] Abou-Shaara, H.F. (10/01/2014). “The Foraging Behaviour [9] “Histone Modications.” W hat Is Epigenetics?. of Honey Bees, Apis Mellifera: a Review." V eterinarni www.whatisepigenetics.com/histone-modications/. Medicina. 1-10 . Retrieved; 11/05/18. Retrieved; 16/05/18.

[3] Frisch, Karl von, and Leigh E. Chadwick. (1993). “The [10] (17/05/2018). “Histone Modications: a Guide.” A n Dance Language and Orientation of Bees. Harvard Overview of Insulin Signaling Pathways | Abcam. University Press. Retrieved; 11/05/18. www.abcam.com/epigenetics/histone-modications-a-guid e. Retrieved; 17/05/18.

[4] (27/08/2014). “Honey Bee Biology.” E Xtension. [11] (2015). “Mushroom Bodies.” E gyptian Journal of Medical articles.extension.org/pages/71148/honey-bee-biology#.U_- Human Genetics. Wo3bp8_c. Retrieved; 13/05/18. www.sciencedirect.com/topics/neuroscience/mushroom-b odies. Retrieved; 17/05/18.

[5] (27/08/14). “Biology of Individual Honey Bees.” E Xtension. [12] “Learning and Memory - the Mushroom Body.” J anelia articles.extension.org/pages/21739/biology-of-individual-ho Research Campus. ney-bees#.U_3swsVdU7k. Retrieved; 14/05/18. www.janelia.org/lab/rubin-lab/our-research/anatomical-an d-behavioral-analyses-brain-areas/learning-and-memory. Retrieved; 17/05/18

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[6] (27/08/18). “Bees and Social Instincts.” E Xtension. http://articles.extension.org/page [13] (20/03/2017). “Neuroscience: Intelligence in the s/21759/bees-and-social-insects#.U_3tBcVdU7k. Retrieved; Honeybee Mushroom Body.” E gyptian Journal of Medical 14/05/18. Human Genetics. www.sciencedirect.com/science/article/pii/S0960982217301 471 . Retrieved; 17/05/18.

[7] Bali, Purva, et al. (06/2011). “Methylation, Memory and Addiction.” A dvances in Pediatrics. [14] Lie, Jon. (12/11/2012). “The Remarkable Bee Brain.” J on www.ncbi.nlm.nih.gov/pmc/articles/PMC3142366/. Lie, M.D. jonliemd.com/blog/the-remarkable-bee-brain-2. Retrieved; 16/05/18. Retrieved; 17/05/18.

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・ GENERAL NEUROSCIENCE・ –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– The Neuroscience Behind Imagination, or What We Imagine it to be Kimaya Gadre

Abstract

The word imagination came from the Latin word ‘imagio’ or ‘imagin’, which simply means ‘image’. This word soon evolved and became ‘imaginari’, which means ‘to imagine oneself’. We have changed and edited this word and its meaning to such an extent that it now means ‘the faculty or action of forming new ideas, images or concepts of external objects not present to the senses’. Only recently has imagination been studied from a neuroscientic perspective, so very little is known about it. The neurological process that allows us to imagine things is not clear, with much debate surrounding the many theories within the eld of cognitive neuroscience. Going back to the denition of imagination, it is arguable that the denition is partially incorrect, and in fact, some of the theories for the neuroscience of imagination go against that denition.

Imagination and The Senses

Most people have seen a dog, and most people have seen a dinosaur (a picture of one), but not many have seen a dog riding a dinosaur. Can you imagine it though? If you try, you’ll nd that it’s certainly possible, but how exactly does the brain combine these two images to create something it has never seen before? The exact details of how we imagine things is not well-known, but we know that it has a lot to do with both the ve senses and memory.

When you look at a dog, for example, a group of neurons related to dogs, called a neuronal ensemble, in the posterior cortex activates and then goes on to activate the visual cortex, which resides primarily in the occipital lobe [1]. When you imagine a dog, we see that many of the same areas of the brain “light up” or are activated. The key dierence between seeing and imagining is that the medial temporal lobe and hippocampus, areas involved in memory, are activated instead of the visual cortex [2]. But this only works if we are using our memory to remember a dog we have already seen. How do we imagine something completely new, like a dog riding a dinosaur? The “Mental Synthesis Theory” proposes an answer for this.

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The “Mental Synthesis Theory”

The “Mental Synthesis Theory” states that if the neuronal ensemble for a dog and that for a dinosaur are activated at the same time, then it is likely that the two will overlap, appearing as a single object, and you will see a dog riding a dinosaur. It is thought that the prefrontal cortex coordinates the neuronal ensembles that are activated at the same time in the posterior cortex. The distance between each ensemble and the prefrontal cortex is not always the same, so how does the message reach both at the same time? It is thought that dierences in the amount of myelination within each pathway may explain this phenomena. Myelin can speed up the transmission of action potentials by 10, 100, or even 1000 times, so if a proximal destination has a lightly-myelinated pathway from the prefrontal cortex and a distal destination has a heavily-myelinated pathway from the prefrontal cortex, the message can still reach both destinations at the same time.

Once two things, such as a dog and dinosaur, are imagined together for the very rst time, the amount of myelination on these pathways may change in order for the action potential to reach both neuronal ensembles at the same time [1]. This occurs because the prefrontal cortex expects one to imagine these two objects together multiple times and tries to synchronize the ring. The “Mental Synthesis Theory” has helped us understand how we recall objects from our memory and incorporate them into our imagination.

Imagination and Creativity

It is thought that approximately half of our neurons sense the environment (sensory neurons) and the other half react to stimuli from it (motor neurons) with multiple possible paths from a single sensory neuron to a single motor neuron. Most extra paths are unnecessary links leftover from pruning during the development of the nervous system and are not very active or useful to us. Or so we think. In reality, these excess pathways are thought to be where random creative ideas stem from [3]. Much is still unknown about this theory, but it seems that creative thoughts are the product of interaction of many parts of the brain and mainly the cooperation of the Default Mode Network and the Central Executive System [4]. The Default Network is a group of brain regions that show lower levels of activity when engaged in a particular task, such as paying attention, and higher levels of activity when we are awake and not involved in any specic mental exercise, but rather daydreaming, recalling memories, imagining the future, or just “thinking" without any explicit goal. The Central Executive System is responsible for the control and regulation of cognitive processes. It coordinates working memory and long term

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–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– memory. The Default Mode Network and the Central Executive System work hand in hand to create our random thoughts, which may develop into creative and innovative ideas.

Imagination and Hallucinations

Hallucinations have been dened as ‘perceptions in the absence of an external stimulus and are accompanied by a compelling sense of their reality.’ Hallucinations and imagination can be easily mistaken for each other, but there are some main dierences to help distinguish them. While hallucinations are sensations that appear real to the person experiencing them, most of us know that what we perceive through our imaginations are not real. Though we can dierentiate between these two experiences, the processes behind them are not fully clear to neuroscientists. Imagination is caused by a specic, external stimulus at some stage, while hallucinations are often signs of an illness, and their origin or why they occur is not very well understood. Additionally, people do not have control over their hallucinations but do have at least some control over their imaginations [5].

Conclusion

Going back to the denition of imagination (‘the faculty or action of forming new ideas, or images or concepts of external objects not present to the senses’), we see that it may be incorrect from a neuroscientic perspective, since usually one is not forming original ideas, but rather one is piecing together objects like pieces of a puzzle to form a ‘new’ idea. Imagination seems to always involve familiar pieces and never completely foreign objects; however, in saying that, we have only seen the tip of the iceberg of imagination. Although we do not currently know much about imagination, through research and further experiments we can uncover the true and complete process of imagination and the reason behind this fascinating process.

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References

[1] Andrey Vyshedskiy PhD, Tomás Pichardo-Espaillat. (12/12/16). [4] Vanessa Hill, Bahar Gholipour. (18/01/18). The neuroscience of The neuroscience of imagination. Retrieved; 01/07/2018. creativity. Retrieved; 07/07/2018.

[2] Luigi F Agnati, Diego Guidolin, L. Battistin, G. Pagnoni, K. [5] Patricia Boksa PhD. (15/07/09). On the neurobiology of Fuxe. (24/05/13). The neurobiology of imagination: possible role of hallucinations. Retrieved; 10/07/18. interaction-dominant dynamics and default mode network. Retrieved; 03/07/2018.

[3] ImagiRation, Andrey Vyshedskiy PhD. (17/12/14). Neurobiology of imagination and language acquisition critical period- The Mental Synthesis Theory. Retrieved; 04/07/2018.

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・G ENERAL NEUROSCIENCE・ –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Neurolinguistics: The Intersection of Language and the Brain Geetanjali Rastogi Abstract:

This article aims to provide an introduction to neurolinguistics, a subcategory of linguistics which is broadly concerned about the structure and use of language [3]. It is also related to psycholinguistics, which focuses on the relationship between language and psychological processes such as language acquisition [10]. This article explores brain structures involved in language production and comprehension, disorders of those structures, prominent research in the eld, and areas where there is a lot more to be discovered.

Brain Structures Associated With Language

The two parts of the brain that are most often associated with language are Wernicke's area, which is in the temporal lobe on the left side of the brain and is responsible for the comprehension of speech, and Broca's area, which is in the frontal lobe and is involved in the production of speech. Recent evidence, however, suggests that language in the brain is much more complex and plastic, being processed in many dierent areas. Even a single word can engage multiple parts of the brain: we use sensory cues, emotional cues, and context cues to think of and verbalize a particular word, all of which occur in dierent areas of the brain. Interestingly, the majority of the parts of the brain linked to both spoken and written language are in the left hemisphere of the brain, regardless of what language one reads and how it is written. This is most notably demonstrated by the fact that aphasia, or cognitive language loss, is almost always caused by injury to the left hemisphere, not to the right hemisphere. This observation can be seen across dierent languages and dierent reading/writing abilities [8].

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Neurolinguistic Disorders

A prominent condition associated with neurolinguistics is aphasia, the cognitive loss of language. It can develop suddenly, such as in the cases of a stroke or sudden head trauma, or over time, such as due to a brain tumor or progressive neurological disease. The disorder aects all aspects of language: comprehension, speech, reading, and writing. It may interact with other neurological disorders. Aphasia typically aects the middle-aged and elderly, but it can occur in anyone. It currently aects about three-thousandths of the US population [1].

There are many types of aphasia, including Wernicke's aphasia (caused by damage to Wernicke’s area), where the patient may speak in long, nonsensical (but often grammatically correct) sentences embellished with superuous or even made-up phrases. Patients’ ability to comprehend spoken and written language is usually severely impaired, however. Something someone with Wernicke’s aphasia might say is "You know that smoodle pinkered and that I want to get him round and take care of him like you want before," which could simply mean, “I want to walk the dog.” Damage to Broca’s area results in Broca’s aphasia. Patients retain relatively normal levels of comprehension, in contrast to Wernicke’s area, but are only able to produce short, broken phrases [1]. Those with Broca’s aphasia are also more likely to be aware of their speech issues, so they can be more frustrated. An example of a sentence that someone with Broca’s aphasia might say is “Walk dog,” which could mean “I walked the dog,” “You should walk the dog,” or something similar [1].

The brain is remarkable in its ability to heal itself, but still, people may require extra measures to live comfortably with a disorder like aphasia. Speech-language therapy is often used in aiding patients to learn how to communicate again. This includes the encouragement of using remaining communication methods and acquiring new methods of communication. The brain’s plasticity helps communication abilities to return to normal even though some brain areas may be damaged. Responsibilities may be shifted to other brain areas, but aphasia can never be fully cured [1].

Another familiar linguistic disorder thought to have neurological origins is dyslexia, or diculty reading or interpreting text while being generally intelligent. It aects 20 percent of the population and represents 80 to 90 percent of all those with learning disabilities. Individuals with dyslexia use dierent parts of the brain to process text than those without it, and these parts do not function as eciently during reading as the parts of the brain that non-dyslexics use. Specically, the o ccipito-temporal, temporo-pa rietal, and inferior frontal cortices, which are involved in reading, are altered in individuals with dyslexia; less gray and white matter volume can be found in these areas [14].

Like aphasia, dyslexia cannot be cured, but with the correct accomodations, it can be eectively adapted into one’s lifestyle. Those with dyslexia often require extra, distraction-free time on tests, text-to-speech technology, and the ability to write notes on laptops in order to succeed in a classroom environment. Teachers can facilitate reading in children with dyslexia by emphasizing speech sounds in words (called phonemic awareness) and letter-sound

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correspondences (called phonics) [2]. It is important to note that the manifestation of the disorder can widely vary, and current dyslexic theories are being considerably upended as a result of new perspectives and ndings.

Developments and Frontiers

Before the development of modern technologies, important discoveries in neurolinguistics were made through lesion analysis, or examining the behaviors of individuals with brain lesions. Broca’s and Wernicke’s areas were discovered through this method. Still, because of the potential ethical issues involved in these study methods, the number of subjects for such studies were limited, and broad conclusions could not be made. Since then, scientists have engaged in more rigorous studies of the brain, using advanced imaging techniques that allow active, instead of deceased, brains to be studied. Many emerging methods (e.g., PET, fMRI, magnetoencephalography, high eld event-related encephalography, and optical imaging) allow healthy brains to be studied directly, eliminating the potential misconceptions produced from applying conclusions from lesioned-brain data sets to normal-brain data sets [4].

One of the more modern, practical aspects of neurolinguistics is the studies of the eects of multilingualism. In this globalized economy, being uent in more than one language is an asset for job prospects and cultural undertakings. Research now corroborates the value of multilingualism in cognitive realms as varied as standardized test-taking to decision-making [6]. Additionally, researchers found that the earlier and more languages a child learns, the more quickly and eciently they will be disposed to learn new information and the more adaptable their brain will be to such incoming information [7]. This information is useful to parents and educators who seek to broaden children’s cultural horizons as well as employers who look to expand businesses to places where languages other than English are spoken.

The future of neurolinguistics is rather promising. Exciting research is being done in relation to music and other forms of expressions as well as brain structures previously thought to control only language abilities [8]. There is more work to be done in regard to the understanding of the physiology of brain structures and processes implicated in linguistics,

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including those at the microscopic level (e.g. neurons and synapses). While neurolinguistic research was previously constrained by technology and ethics, it has been growing exponentially over the last four decades [4]. With jobs in education, research, advertising/marketing, and technology, the eld of neurolinguistics presents many exciting, interdisciplinary job prospects for the future and will continue to grow in prominence as a promising eld of study.

References

[1] (2015). Aphasia. N ational Institute on Deafness and Other [7] Kimppa, L., Kujala, T., & Shtyrov, Y. (2016). Individual Communication Disorders. N IH Pub. No. 97-4257. Retrieved: language experience modulates rapid formation of cortical 07/29/2018. memory circuits for novel words. S cientic reports, 6 , 30227. doi: 10.1038/srep30227. R etrieved: 07/29/2018.

[2 ] Bailet, L.L. (2015). Understanding Dyslexia. KidsHealth from [8] Menn, L. (2012). N eurolinguistics. Linguistics Society of Nemours. h ttps://kidshealth.org/en/teens/dyslexia.html America. Retrieved: 09/01/2018. https://www.linguisticsociety.org/resource/neurolinguistics Retrieved: 07/29/2018.

[3] MacWhinney, B. J. (2001). Psycholinguistics: Overview. [10] What Linguistics and why Study It. The University of International Encyclopedia of the Social & Behavioral Sciences, Arizona.h ttps://linguistics.arizona.edu/content/what-linguistics- 12343-12349. h ttps://doi.org/10.1016/B0-08-043076-7/03024-2. and-why-study-it-0. Retrieved: 07/29/2018. Retrieved: 07/29/2018.

[4] Small, S. L. (2008). The neuroscience of language. B rain and [11] (2018). Wernicke's Area. Wikipedia. Language, 1 06( 1), 1– 3. h ttp://doi.org/10.1016/j.bandl.2008.05.004. https://en.wikipedia.org/wiki/Wernicke%27s_area. R etrieved: Retrieved: 07/29/2018. 07/29/2018

[5] Careers in Linguistics. University at Bualo. {12} (2017). How do PET Scans Work?. The Washington Post. https://arts-sciences.bualo.edu/linguistics/about/careers-in-lin https://www.washingtonpost.com/video/national/how-do-pet-s guistics.html. R etrieved: 07/29/2018. cans-work/2017/07/19/e7b53b56-6c7b-11e7-abbc-a53480672286_vid eo.html?noredirect=on&utm_term=.57d7477cd72a. R etrieved: 07/29/2018

[6] Delistraty, C. (2014). For a Better Brain, Learn Another [13] Kotz, Stahl. R hythm in disguise: why singing may not hold the Language. T he Atlantic. key to recovery from aphasia. PubMed Central. https://www.theatlantic.com/health/archive/2014/10/more-languages- https://openi.nlm.nih.gov/detailedresult.php?img=PMC3187543_a better-brain/381193/. Retrieved: 07/29/2018. wr240f1&req=4. R etrieved: 07/29/2018

[14] Eden, G.F. (2015). Dyslexia and the Brain. Th e International Dyslexia Association (IDA). https://dyslexiaida.org/dyslexia-and-the-brain-fact-sheet/

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・DISEASE・ –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Protein Dysregulation in Amyotrophic Lateral Sclerosis Sarah Shirley

Abstract

Amyotrophic Lateral Sclerosis, also known as Lou Gehrig’s Disease, is a motor degenerative disease that causes loss of motor function. Several mechanisms, such as inammation, prolonged excitation via excess glutamate, and disruption of mitochondrial function, have been proposed to contribute to the pathology of ALS. However, there has yet to be a denite understanding of the pathological mechanism by which Amyotrophic Lateral Sclerosis develops. Protein aggregation has been noted as a pathological trigger of various neurodegenerative diseases, such as Alzheimer’s and Parkinson’s disease [1]. This article investigates the pathological mechanisms in which protein aggregation develops and causes Amyotrophic lateral Sclerosis.

Amyotrophic Lateral Sclerosis Overview

Amyotrophic Lateral Sclerosis (ALS) was rst described in 1869 by the French neurologist Jean-Martin Charcot and ultimately became known as Lou Gehrig’s disease after the famous baseball player was diagnosed with it [2]. With a prevalence of 4-6 per 100,000 people, ALS is a progressive neurodegenerative disorder characterized by the death of motor neurons, which leads to the loss of voluntary movements as well as breathing, eating, or walking complications [3]. This fatal disease leaves the patient with an average lifespan of 3-5 years after onset. The two types of ALS are familial and sporadic, consisting of 5% and 95% of cases respectively [4].

Protein Aggregation

The toxic mechanism that causes Amyotrophic Lateral Sclerosis has long been unknown. Proposed hypotheses have included glutamate toxicity and oxidative distress. Most prominently, the key pathological feature that has been implicated is ubiquitinated protein aggregation, which degenerates motor neurons [5]. Protein aggregation was rst taken into consideration as a main –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 15

–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– contributor of the toxic mechanism of ALS through the discovery of the SOD1 (superoxide dismutase) aggregate in the spinal cord of a familial ALS (fALS) patient [6].

One proposed control machinery that is thought to exacerbate protein aggregation is chaperones, which are upregulated in motor neuron protein aggregates and function in protein aggregation. These molecules have been implicated in the aggregative mechanism and enhanced toxicity of proteins, such as pTDP-43 C-terminal fragments [3]. R eactive astrocytes also have been noted to contribute to protein aggregation. When stressed, astrocytes display changed morphology and properties, thus becoming “reactive.” Co-cultures of astrocytes with motor neurons induce protein aggregation and motor neuron degeneration and survival. Astrocytes, when reactive, increase secretion of inammatory factors along with enhancing excitotoxicity due to excessive postsynaptic stimulation [6].

Characteristics of Protein Aggregates

Predominantly, ubiquitinated protein aggregates are characterized to be Lewy body-like hyaline inclusions (LBHIs), which are randomly oriented laments covered by ne granules or skein-like inclusions. Bunina bodies, characterized by eosinophilic, ubiquitin-negative, round hyaline inclusions without a halo, are surrounded by tubular structures and amorphous dense structures [5]. Some protein aggregative variants are outlined below:

SOD1 is understood to protect cells from oxidative distress and is causative for 23.5% of

familiar and 7% of sporadic cases of ALS. A study from Cornell using pulsed ESR spectroscopy found that copper deciencies from SOD1 mutation cause protein instability through structural deconformation. Mice injected with hSOD1 protein aggregation developed ALS-like symptoms, developing rst in the spinal cord and then progressing to other motor organs after 100 days [7]. In spinal cord samples, SOD1 proteins were found in fALS and sALS patients to be Lewy body-like, brilized, and ubiquitinated {5}.

A notable form of protein aggregation in ALS is TDP-43, which is localized in the nucleus. TDP-43 binds protein to DNA and RNA and has functions of miRNA synthesis and transcriptional repression. Puried TDP-43 depends on the C-terminal glycine-rich domain. Protein inclusions of TDP-43 have been found in the spinal cord, frontal cortex, and glia. They are characterized to be skein-like with hyper-phosphorylated C-terminal fragments [8].

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Further Research

Greater understanding of protein aggregation mechanisms in ALS will aid in developing new therapeutics and targeting strategies for ALS. Questions that should be considered when investigating protein aggregation in ALS include how to suppress and detect protein aggregation in ALS patients. Moreover, dierent structures of protein aggregates from dierent gene variants, along with how protein aggregation interplays with the disease mechanism of ALS as a whole, should be considered.

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[1] Irvine, G. B., El-Agnaf, O. M., Shankar, G. M., & Walsh, D. M. [6] P ratibha Tripathi, et.al (July 13, 2017). R eactive Astrocytes Promote (2008). Protein Aggregation in the Brain: The Molecular Basis for ALS-like Degeneration and Intracellular Protein Aggregation in Human Alzheimer’s and Parkinson’s Diseases. M olecular Medicine, 1 4( 7-8), Motor Neurons by Disrupting Autophagy through TGF-β1. R etrieved 451–464. h ttp://doi.org/10.2119/2007-00100.Irvine from [2] Armon, Carmel. (22/4/2018 ). Amyotrophic Lateral Sclerosis. http://www.cell.com/stem-cell-reports/fulltext/S2213-6711(17)302 https://emedicine.medscape.com. Retrieved May 6, 2018 71-0 [3] Kalmar, B., & Greensmith, L. (2017). Cellular Chaperones As [7] Elaheh Ekhtiari Bidhendi, Johan Bergh, Per Zetterström, Peter Therapeutic Targets in ALS to Restore Protein Homeostasis and M. Andersen, Stefan L. Marklund, and Thomas Brännström Improve Cellular Function. F rontiers in Molecular Neuroscience, 1 0, (2016, June 1). T wo Superoxide dismutase prion strains transmit 251. http://doi.org/10.3389/fnmol.2017.00251 amyotrophic lateral sclerosis-like disease. R etrieved from [4] What is ALS? (n.d.). Retrieved from https://www.jci.org/articles/view/84360 http://www.alsa.org/about-als/what-is-als.html [8] R amesh, N., & Pandey, U. B. (2017). Autophagy Dysregulation [5] Blokhuis, A. M., Groen, E. J. N., Koppers, M., van den Berg, L. in ALS: When Protein Aggregates Get Out of Hand. F rontiers in H., & Pasterkamp, R. J. (2013). Protein aggregation in amyotrophic Molecular Neuroscience, 1 0, 263. lateral sclerosis. A cta Neuropathologica, 1 25( 6), 777–794. http://doi.org/10.3389/fnmol.2017.00263 http://doi.org/10.1007/s00401-013-1125-6

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・RESEARCH・ –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Oxytocin and Social Cognitive Decits: Experimental Treatment of Social Disorders Via Intranasal Hormonal Supplements Tobey Le

Abstract

The factors that contribute to an individual’s ability to engage in a social environment are subtle, complex, and remain largely unknown to the eld of neuroscience. While this may currently be the case, it may not be so for long, as new research has begun to reveal at least one correlating factor: the presence and varying levels of peripheral oxytocin in the endocrine system and blood plasma. The presence of the oxytocin hormone seems to be directly correlated with an individual's ability to read social cues and, more broadly, engage in a social environment. With this knowledge, it may be possible to mitigate the eects of certain mental disorders connected to social cognition, such as autism spectrum disorder (ASD).

Recent Findings and Research

A recent study found that men who tested to have higher levels of oxytocin in their blood plasma had a greater capacity for more uncomfortable social situations, displaying a greater empathy and sociability when presented with various scenarios. Interestingly, these ndings yielded no signicant correlation between said oxytocin levels and the empathy levels of the individuals in question. This of course seems counterintuitive, given that the ability to empathize and pick up on social cues are typically considered to be at least loosely related. While more research must be conducted in this eld before any concrete conclusions can be drawn, the researchers speculate that this apparent disconnect exists because oxytocin exists and functions at the subconscious level, whereas the act of empathizing may require a more conscious eort [2].

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Another study conducted on the subjects found that individuals with higher levels of oxytocin in their systems tend to seek out more social situations and stimuli. The individuals tested in the study were presented with two rooms, each containing two stimuli that were either both social (two chairs) or both non-social (a table and plant), with the distance between the two stimuli diering between the two rooms. Individuals who tested to have higher levels of oxytocin chose rooms with shorter distances between the stimuli, but only when the stimuli were social. The researchers found no correlation between oxytocin levels and preference for distance between non-social stimuli, strengthening the theory that oxytocin governs social cognition and willingness to allow others into their personal space [3].

Intranasal Sprays: Pseudo-Medicine or Legitimate Treatment?

Given these recent ndings, the next logical step was to move into medical trials and determine whether supplementing the endocrine system of someone with social cognition decits, such as an individual diagnosed with Autism Spectrum Disorder (ASD), would meaningfully benet their lives. The relevant research that followed seemed to point to this being exactly the case. One study found that adults with ASD asked to perform social-cognitive tasks performed 63% better after receiving low doses of oxytocin (8 international units) intranasally [4]. Because this oxytocin dose did not have a major eect on peripheral oxytocin levels in blood plasma, it appears that this improvement in social cognition does not imbalance the body’s hormone levels in general. Another study found that a similar low dose of intranasal oxytocin caused children suering from ASD to experience heightened activity in the brain’s mesocorticolimbic systems, improving their ability to anticipate and respond to rewards in their environment [5]. All studies conducted used a bioluminescence enzyme immunoassay to test the levels of oxytocin in the participants [6].

Conclusion

Looking to the future, intranasal oxytocin oers a promising branch of treatment for those suering from disorder-induced social cognition decits. However, progress through the FDA’s safety checks and requirements remain slow, and oxytocin supplements may require several years to arrive at the medicinal market.

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References

[1] No author. (03/11/2015). The Hormone Oxytocin. ZME Science. [5] Greene, R. K. Spanos, M. Alderman, C. Walsh, E. Bizzell, J. https://www.zmescience.com/research/studies/oxytocin-thc-social-in Mosner, M. G. Kinard, J. L. Stuber, G. D. Chandrasekhar, T. ractions-8273234/. Retrieved: 30/03/2018. Politte, L. C. Sikich, L. Dichter, G.S. (27/03/2018). The Eects of [2] Deuse, Lisa. Wudarczyk, Olga. Rademacher, Lena. Kaleta, Peter. Intranasal Oxytocin on Reward Circuitry Responses in Children Karges, Wolfram. Kacheva, Stella. Gründer, Gerhard. Lammertz, With Autism Spectrum Disorder. Journal of Sarah E. (28/03/2018). Peripheral Oxytocin Predicts Higher-Level Neurodevelopmental Disorders. Social Cognition in Men Regardless of Empathy Quotient. https://www.ncbi.nlm.nih.gov/pubmed/29587625. Retrieved: Pharmacopsychiatry. 30/03/2018. https://www.ncbi.nlm.nih.gov/pubmed/29590682. Retrieved: [6] Karasawa, Koji. Sano, Yoshihiro. Kato, Nobumasa. Arakawa, 29/03/2018. Hidetoshi. (07/03/2018). Development and Clinical Application of [3] C ohen, D. P erry, A. M ayseless, N. K leinmintz, O. a Bioluminescence Enzyme Immunoassay for Oxytocin. Shamay-Tsoory, S. G. (13/03/2018). The Role of Oxytocin in Implicit Luminescence: The Journal of Biological and Chemical Personal Space Regulation: An fMRI Study. Luminescence. h ttps://www.ncbi.nlm.nih.gov/pubmed/29512944. Psychoneuroendocrinology. Retrieved: 30/03/2018. https://www.ncbi.nlm.nih.gov/pubmed/29601981. Retrieved: 31/03/2018. [4] Quintana, D. S. Westlye, L. T. Hope S. Nærland, T. Elvsåshagen, T. Dørum, E. R ustan, Ø. Valstad, M. Rezvaya, L. L ishaugen, H. Stensønes, E. Yaqub, S. Smerud, K. T. Mahmoud, R. A. Djupesland, P. G. Andreassen, O. A. (23/05/2017). Dose-Dependent Social-Cognitive Eects of Intranasal Oxytocin Delivered With Novel Breath Powered Device in Adults With Autism Spectrum Disorder: A Randomized Placebo-Controlled Double-Blind Crossover Trial. Translational Psychiatry. https://www.ncbi.nlm.nih.gov/pubmed/28534875. Retrieved: 30/03/2018.

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・NEUROTECHNOLOGY・ –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Brain versus Computer: A Comparison of Structure, Methods, and Capabilities Khayla Black

Abstract

Two of the most powerful processing tools in today’s society are the human brain and the computer. Though they have some dierences in information processing, memory and recognition, and basic functional units (neurons and transistors), scientists are working to bridge the gap between them. Both are practical and powerful tools for everyday application, but will the computer ever be able to catch up to the capabilities of the human brain, in regards to processes such as facial recognition and self-reection? A comparison of the brain and modern computers highlights the dierences between the two and suggests that, in the future, they may cease to exist.

Introduction

The computer is currently one of the most powerful tools for computation. With its enormous computational abilities, how does the brain compare to the computer? With enhanced problem-solving capabilities and a basic operation speed one million times faster than that of the brain, it is not unreasonable to assume that the computer may have more capabilities even beyond those of problem solving. However, the brain’s recognition abilities and power consumption contribute to its success over computers in certain endeavors. With an increase in machine learning techniques, research, and its application to biology, it is essential that the computer and the brain are compared and their similarities and dierences analyzed. Through further research, we may be able to develop and apply new technologies to old problems such as disease diagnosis.

Similarities

A modern computer and a human brain resemble each other much more than they did in 1946 when the ENIAC was revealed to the public [1]. The computer and the brain are both extremely powerful tools utilized in computation, each with their own respective strengths. Both are characteristically precise and extraordinarily quick with regards to computation. Each has its own

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–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– basic unit: something that, while very small on its own, comes together with many other units to form the whole system. For the brain, these are known as neurons, and for a computer, transistors. While both are able to perform computations, each has distinct processing abilities and methods. The transistor is beginning to resemble the brain more with the creation of neural networks, which allow for machine learning. Both the brain and computers can be used for recognition, disease diagnosis, and mathematical computations, with computer-human interaction allowing us to combine the strengths of each system in order to maximize their potentials.

Pros and Cons Between Methods

By examining the various similarities and dierences between a brain and a computer, it is evident that there are pros and cons to each of them. Computers contain up to 10 billion transistors, while the human brain contains 100 billion neurons, providing the brain with much more communicative potential and processing ability; however, a computer has a much higher speed of operation, approximately 10 million times faster than that of the human brain [2]. A computer’s speed, along with its incredible accuracy, is one of the hallmark traits that enable the computer to be compared to the brain; however, these two traits come with a cost: power consumption. While a computer uses 100 watts of power, the brain only uses 10, allowing it to be much more practical for constant use [2]. On the one hand, a computer’s precision and speed allow it to perform complex calculations much quicker than a human brain. On the other hand, they also consume an unrealistic amount of power for everyday application. In contrast to computers, the brain’s greater number of synapses and minimal amount of power consumption provide the perfect conditions for successful and practical operations, but the brain is also much slower and less accurate in a variety of its computations.

Neurons versus Transistors

A brain and a computer dier in their most basic functional unit. The number of transistors that constitute a computer is far fewer than the number of neurons in the brain, and the transistors’ three pins involved in input and output do not even compare to the capabilities of the multitude of dendrites and single axon of the multipolar neurons in the brain. However, a recently developed transistor that has been modeled after a neuron shows promise in mimicking certain aspects of neuronal function [3]. One of the most dicult aspects of a neuron to imitate are the weighted inputs, but this new transistor has been shown to utilize weighted summation and threshold functions that mimic the way that neurons receive weighted input signals from neighboring neurons, sum the input, and compare it to a threshold value to determine whether or not to re [3]. This advancement in technology shows promise in the endeavor to create a computer resembling synapses, which will only contribute to the computer’s eectiveness by turning one of the computer’s fallacies into one of the brain’s strengths.

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Memory and Recognition in Machine Learning

As technology advances, many scientists are developing ways to integrate learning and memory into machines. The simplest model of a neural network, the perceptron, emphasizes this development and its capabilities. A perceptron displays connections and associations rather than topographic representations, works to determine a current response with knowledge of what has occurred in prior experiences, and aims to reinforce old connections. Each of these components are modeled o of our current model for learning and memory in the mammalian brain [4].

A perceptron has a few rules of organization that contribute to its capabilities. Perceptrons respond with a frequency proportional to their stimulus intensity and on an all-or-nothing basis, similar to a mammalian neuron [4]. Additionally, impulses are transmitted to a set of association cells in a projection area, which receive various connections from sensory points. These sensory points will then transmit impulses to the origin point which is either excitatory or inhibitory, similar to neurons [4]. After this, the summation values are then compared to a threshold value which will determine the response, similar to the decision of whether or not to re in the brain [4].

The simplest model of a perceptron is comprised of a single layer, but there are also multilayer perceptrons that have much more profound abilities. For example, the multilayer perceptron has been employed to determine criteria for the start site in E scherichia coli, which is signicant in disease diagnosis [5]. The multilayer perceptron has also been utilized to diagnose and evaluate Alzheimer’s disease through the analysis of weighted magnetic resonance images [6]. The biological applications of neural networks have had a signicant inuence in the eld of biology and demonstrate the similarities between the capabilities of a computer and a human brain.

Information Processing

One point of distinction between computers and brains is processing method. For example, computers lack many of the recognition capabilities that humans possess, which may be attributed to the fact that computers operate using pixel-by-pixel processing as opposed to synaptic connections [7]. This may contribute to a computer's inability to recognize facial features to the same degree that the mammalian brain is able to. Computers do not take in an entire image as the brain would, but rather segments and pieces, which prevent them from seeing the entire picture. For example, if a device utilizes facial recognition to unlock, it is not uncommon for it to only respond to one segment of the face. Alternatively, when humans encounter a close relative, they do not need to see a certain segment of their face the recognize them. Recognition is not the only dierence in

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–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– processing capabilities. Rather, humans and computers dier in nearly every aspect of their processing including control, input, output, storage, and self-processing capabilities.

Computers utilize a central processing unit (CPU) which lends itself to a form of more centralized control, while brains generally use a hierarchical system which allows for greater division of work. Central processing allows for a greater level of control, as the computer knows what is going on at each point in time [7]. Such a system would not be practical in the context of a brain, as the failure of the central unit would create chaos and failure in the entire system, which is evidently not favorable for human function. Instead, a brain’s hierarchical system allows for a systematic level of processing and division of work that does not place too much pressure on one single unit in the brain [7]. In other words, if one area fails, the system as a whole will continue to operate.

Brains and computers also dier in their input-processing methods. Computers employ a form of sequential, or serial, processing, processing one thing after another, while the brain employs a parallel processing method where many units can be processed simultaneously [7]. For example, when light enters the eye, it is being processed simultaneously by many dierent photoreceptors, so each cell in the retina has already begun to process visual information before it ever exits the eye [7]. This dierence in processing may explain some of the dierences in recognition capabilities between computers and brains. The refractory period in the brain would only allow for 100 sequential steps which is not sucient for computational pattern recognition [7].

Likewise, the methods for dealing with outputs and overwriting also dier between the two. Computers utilize locks for output which prevent them from accessing various documents simultaneously: only one function is employed at any point in time [7]. This is necessary or else overwriting would occur [7]. However, with regards to the brain, systems are said to overlay each other. This prevents new responses from replacing the old ones, another form of overwriting. This prevention is extraordinarily advantageous since older systems can oftentimes be more reliable and can take over in the event that newer systems fail [7][8].

The last notable dierence to be mentioned is the capability of self-processing - what we commonly refer to as consciousness. While humans form impressions of themselves, a computer is unable to do this and has no form of self-processing or self-awareness. This may be a disadvantage since this ability in humans allows for the creation of goals and change and brings about a certain level of self-awareness. This may be a key aspect in developing technology able to imitate human cognition.

Limitations of Computers

Though computers display impeccable precision, there are many limitations on a computer too. For example, connection modication in the computer has not even come close to resembling such modication in the brain. Learning and memory in organisms are thought to take place in synaptic connections. Throughout various experiences, an individual is able to modify its response to various circumstances and activities, whereas a computer is unable to do this at a comparable level,

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–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– since weighted inputs are just now being utilized in transistors. Neural networks have been created, which associate certain responses with various weights in order to develop a method for machine learning; however, the technology is new and is still a work in progress. Their capabilities are limited when compared to the human brain [8]. The presence of such technology suggests that in the future with adjustments to this technology, computers and machines may have similar modication abilities to those of the mammalian brain.

An additional limitation of computers is their CPU. The brain does not have a CPU, but rather a systematic way of reporting information. A centralized unit of stored information creates a risk: if the processing unit fails, then all information is lost and the system as a whole fails. The brain safeguards against this with its characteristic plasticity: the ability to adapt or change over time. For example, when an individual suers from brain damage, such as stroke, sometimes there are methods of recuperation. In some cases, especially involving younger people, each part of the brain can work together to compensate for what was lost. Had this been a computer, the entire system would have shut down and would not be able to be restored without external assistance.

Disadvantages of the Brain

Similar to the computer, the brain has its own limitations which inuence its computational abilities. One of these is precision. The brain does not even compare to the computer in terms of its precision. Take, for example, a simple math problem. A computer will perform the calculation and round to any desired degree without any error; in fact, machines can achieve any level of desired precision {8}. This lack of precision proves to be a major limitation in the human brain. Aside from precision, the brain’s most signicant limitation may be speed. Ironically, this limitation of the brain is one of the fundamental advantages of the computer. Computers are known to use serial methods to improve their speed. Essentially, in computations such as mathematical calculations, one decision is needed before the next one can be made, and this is the key to the success of the computer. While humans employ parallel processing, the serial processing of the computer allows for success upon considering the fact that a computer can do millions of operations per second, whereas the brain can do approximately ten decisions per second {7}. Not only does the brain use parallel processing, but it is not even capable of employing rapid serial processing, contributing to its slowness in its computations. Another issue with computation in the brain is its inability to handle multiple variables. While the brain struggles with more than two, the computer can be programmed to handle many variables simultaneously {7}. These limitations of the brain not only contribute to its computational disadvantages, but also highlights scenarios where the computer is much more advantageous for computational purposes.

Conclusion

The human brain and the computer both have remarkable capabilities, though they have many similarities and dierences. With their utilization of a basic output, their expedient and precise

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–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– computation, and their utilization of learning and memory, they are both able to accomplish many similar tasks. However, each has its respective pros and cons. Currently, computers are approximately one million times faster than the human brain and have a much greater accuracy, whereas the brain has a substantially greater number of synapses, allowing for more ecient processing, less power usage, and greater recognition capabilities. Though neurons and transistors are fundamentally dierent, transistors are beginning to more closely resemble neurons by assigning weights to outputs and allowing for comparison to threshold values in order to decide whether or not ring is appropriate. This may lead to more functional processing in computers that is comparable to the parallel processing that occurs in the brain as opposed to the sequential processing that computers currently utilize. The future certainly holds much more research and growth in the elds of computer science and neuroscience and gives reason to believe that a computer will someday be able to mimic, or even surpass, the abilities of the human brain.

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References

[1] Vasilescu, I. Programming the ENIAC. Retrieved from [5] Tarca, A. L., Carey, V. J., Chen, X., Romero, R., & Drăghici, Columbia University. S. (2007). Machine Learning and Its Applications to

http://www.columbia.edu/cu/computinghistory/eniac.html Biology. P LoS Computational Biology, 3 ( 6), e116. h ttp://doi.org/10.1371/journal.pcbi.0030116

[2] Luo, L. (2018, April 12). Why Is the Human Brain So Ecient? [6] Saniotis, A., Henneberg, M., & Sawalma, A.-R. (2018). - Issue 59: Connections. Retrieved Integration of Nanobots Into Neural Circuits As a Future from h ttp://nautil.us/issue/59/connections/why-is-the-human- Therapy for Treating Neurodegenerative Disorders. F rontiers in brain-so-ecient Neuroscience, 1 2, 153. h ttp://doi.org/10.3389/fnins.2018.00153

[3] Zyga, L. (2017). Neuron transistor behaves like a brain neuron. [7] Whitworth, Brian & Ryu, Hokyoung. (2007). A Comparison Retrieved from of Human and Computer Information Processing. https://phys.org/news/2017-06-neuron-transistor-brain.htm

[4] Rosenblatt, F. (1958). The perceptron: A probabilistic model [8] Solomon, Srunodhayan Sam. “Superiority of the Human for information storage and organization in the Brain over the Computer World in Terms of Memory, Network, brain. P sychological Review, 65( 6) Retrieval and Processing.” A merican Journal of Engineering 386-408. h ttp://dx.doi.org/10.1037/h0042519 Research, vol. 3, no. 5, 2014, pp. 230–239., www.ajer.org/papers/v3(5)/ZB35230239.pdf.

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・I NTERVIEW・ –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– An Interview With Elisabeth Glowatzki: Departments of Otolaryngology and Head and Neck Surgery and Neuroscience at Johns Hopkins University Dharshan Varia

Abstract

I sat down with Dr. Elisabeth Glowatzki, Professor of Otolaryngology and Head and Neck Surgery and Neuroscience at the Johns Hopkins School of Medicine to talk about her role, education, innovation, and projects she’s currently conducting in neuroscience, including teaching, research, and physiology. Dr. Glowatzki is currently investigating the function of auditory nerve bers in the mammalian cochlea. Other projects in her lab involve eerent synaptic transmission and supporting cell function in the cochlea.

Dharshan Varia (DV): “What do you do on a daily basis? What is your role in the eld of neuroscience?”

Elisabeth Glowatzki (EG): “To the rst question, I do three things. One is teaching, which is when I present lectures, give courses, but also do one-on-one teaching to graduate students and postdoctoral fellows. Secondly, I design research studies together with the people in my laboratory. Thirdly, I write grant applications, so we have funding, and I write publications based on what we do in the lab. My role in the eld of neuroscience is that we specically study hearing, and we look at synaptic transmission in the auditory pathways of the inner ear.”

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DV: “From when you rst started studying, what inspired you to become a neuroscientist?”

EG: “I studied in Germany, biology, and I was always attracted to understanding how the brain works, so I decided to specialize in neuroscience. Then, it was a talk by a prominent hearing scientist, and his name was Jim Hudspeth. He works in New York. He came to Germany to give a lecture about how the inner ear works, and I was very inspired by that, and that moved me into the eld of hearing.”

DV: “In your tenure as a neuroscientist, how has neuroscience education changed? How are the labs dierent abroad than here at Johns Hopkins?”

EG: “It has changed a lot, especially, since I am from Germany. The neuroscience education that I experienced was very classical and wide in the eld. However, now, if you study neuroscience you will be trained in many dierent techniques rather than a lot of background I received. The background you now receive is very specic to the newest methods; for example, in the last few years, genetics has become a very important factor in the eld of neuroscience, and beforehand, that was not the case. There is no dierence in the labs here and Germany.”

DV: “What are some technological innovations in neuroscience at Johns Hopkins today?”

EG: “In my laboratory, we were the rst laboratory to actually be able to record the synaptic activity of auditory nerve ber endings worldwide. This has allowed us to exactly look how the signal that the hair cells receive about sound information will be processed in the auditory nerve bers. Here at Hopkins, and in our center, there are many studies that really advance the eld. One I would really like to mention is the work by Charley Della Santina and his colleagues because they work on vestibular prosthesis, which like a cochlear implant, will allow to replace the sensory hair cells in the vestibular system. People with balancing problems and Meniere's disease will hopefully benet from this.”

DV: “How have your auditory synaptic nerve endings directly beneted hearing loss today?”

EG: “It is not a straight line. Basically, when we think about hearing loss, one thing we need to understand, there are many dierent contributing factors. For dierent people, dierent things arise. One prominent problem one can experience with hearing loss is that the auditory nerve ber endings die; it’s called synaptopathy. It will happen if you perceive a sound that is too loud or with aging. Synaptopathy will give you problems when you try to understand sound signals. So, what we are working on is to understand how auditory nerve bers work and to be at some point with other groups together replace neurons and make new neurons that produce the right synaptic contacts for an ear that has a loss of hearing due to synaptopathy.”

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DV: “With all of your fellows and graduate students, what projects are you currently undergoing in your lab, and what importance does neuroscience have in your experiments?”

EG: “All what we do is neuroscience because we study the inner ear, which is a neuronal structure and sends basically nerve signals to the brain. What we are doing right now is specically working on nerve bers that possibly get activated by sound signals and send a signal back to the inner ear. What we think is that those nerve bers are protecting our inner ear during loud sounds. That is something that our brain does itself. We want to understand how the brain protects the inner ear from sound exposure. If we understand that, we could use this mechanism to produce a protective method for the inner ear.”

DV: “How do you, as a neuroscientist and professor of otolaryngology, connect/interact with other members within the neuroscience, otolaryngology, and neurosurgery elds?”

EG: “I attend lectures in both departments, so I also have collaboration with colleagues in both departments. I teach neuroscience students who get their doctoral degree. I am involved in their exams, so I am part of the neuroscience community. What is very special for me is that I am also in a clinical department. I really know the physicians well that are specialized in their elds, looking at either hearing or balance dysfunction. The communication between the basic scientists and the clinicians is very important to rst decide what is a really important question in the eld that needs to be answered to make out comes better when teaching patients, so we can learn from each other. For example, we have big cores that every year we put together. I have been the director of this from the inner ear up to the brain and every stage in between. It has a mix of neuroscientists that give lectures and are specialized. Also, clinicians that tell us about the disease that specically arise in the auditory or vestibular pathways.”

DV: “How crucial is it for neuroscience students (those interested in neuroscience) to research and have lab skills in their undergraduate, postgraduate, and possible medical education?”

EG: “To really understand how research works, one denitely needs to work in a laboratory. It takes a number of years not just to even learn all the practical skills, but also to be able to judge good research. Also, to understand how research design happens and how many pitfalls there are during your studies that you have to take care of. In that sense, there are some subspecialties which analyze data they did not gain themselves, which makes sense if you are doing computational studies. Otherwise, you really have to work in a laboratory to understand how research works.”

DV: “Through your tenure as a professor and all of your research work, what has been your biggest challenge?”

EG: “I think the biggest challenge is having a laboratory that is continuously moving forward. We work with students and postdoctoral fellows who come for a few years and sometimes it –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 29

–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– takes them three to four years until they are at the point to do good research. Just when they are ready to really excel they move on. One thing one has to be really good at is that all of the technological advancements stay in the laboratory by teaching and making sure that the next generation learns from the last; there is always overlap. Having change in personnel can be an advantage because after a certain time one has a certain view of a project; new people can change this view and bring something new. It is a challenge and an advantage.”

DV: “What has been your most signicant nding in neuroscience?”

EG: “Our most signicant is what I talked about: we are the rst group worldwide that was able to actually look at the synaptic activity in auditory nerve bers that sent sound signals to the brain. There is a subgroup of auditory nerve bers; they are called the Type II bers, where it is completely unknown as to what this group of bers does. We are the rst group that has looked at any activity patterns of these auditory nerve bers. We are still trying to gure out what their function is.”

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References

[1] Glowatzki, Elisabeth. (n.d.). Neuroscience Department. Johns Hopkins School of Medicine. http://neuroscience.jhu.edu/research/faculty/32.Retrieved: 08/07/2018

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・INTERVIEW・ –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Zebrash and Hearing: An Interview with Dr. Allison Con Chinmayi Balusu

Introduction

Dr. Allison Con is an associate professor of neuroscience at Washington State University, Vancouver. Dr. Con is interested in sensory biology, specically in how sh sense their environment and how they hear. Dr. Con’s focus is on using sh to understand more about our own hearing, including protecting our hearing. In this article, she answers questions about her research, which is primarily based on how larval zebrash respond to loud noises or damaging drugs. Dr. Con also talks about her path to pursuing research in hearing and the importance of the eld [1].

Chinmayi Balusu (CB): How did you become interested in neuroscience? What made you become interested in hearing specically?

Dr. Allison Con (AC): Actually, I didn't start out being interested in neuroscience. My interest in hearing led me to neuroscience, and that all came through my interest in sh. I started out wanting to study marine biology; I went to college for marine biology in Florida, and while I was there, I learned that some sh can produce sound to communicate with each other. For some reason, the idea of noisy sh talking to each other underwater just fascinated me. I wanted to know more about how the sh could do that. If the sh could make sound, did that mean that they could hear what the other sh were saying? It never even occurred to me that sh have ears because we don’t see their ears.

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I did my Ph.D. studying sh hearing. It was during that time that I learned how we can use sh as a biomedical model to understand our own hearing as well, and I dove into neuroscience. It was a very circuitous, windy, yellow brick road.

CB: That’s very interesting! Are there certain types of sh that are easier to research hearing in?

AC: There denitely are! In my lab, we mostly study zebrash. Zebrash are like the mouse or lab rat of the sh world. We study the babies, the zebrash larvae, which are the size of an eyelash. They’re great for studying hearing because they have hearing cells, which are called hair cells. These sh have hair cells in their ears and also on the outside of their body in a system called the lateral line, which helps them detect water moving around them. Since zebrash larvae are really small, we can put an entire sh under a microscope and see all of its hearing cells at once to try to learn more about what they’re doing.

There are some other sh that are also really good to study because while zebrash are great for working in a lab, they don’t actually make sound. There’s another species of sh called the midshipman sh that is found o of the west coast. The male midshipman sh sing to attract females, and the females will pick a mate to breed with based on his song. Midshipman sh are really interesting for studying hearing because we know they need to be able to hear to reproduce, especially since they breed at night.

CB: What are the research questions that you are trying to answer right now in your lab?

AC: One of the big questions in my lab is how the hair cells, hearing cells, of the sh die in response to dierent types of damage. We know that things like loud noise, which cause us to lose our hearing, kill these cells in the sh, and we want to know how that happens. We want to know the dierent biochemical cascades that are activated in these cells to lead to their damage so that we can intervene and develop drug therapies to forgo that damage. We’re asking those questions with dierent types of hearing loss: with noise and certain drugs.

Certain chemotherapy drugs and antibiotics can cause hearing loss by killing hair cells, and we want to know how those drugs damage the hair cells. We want to know how that is similar and dierent when compared to the damage that loud noise does. And, we want to know how we can customize dierent therapies for the dierent types of hearing loss.

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CB: Wow! I never knew that there was a connection between drugs and hearing!

AC: For most of the antibiotics we use, there isn’t a connection with hearing loss. The drugs that you’re going to get if you have a bacterial infection are generally not going to cause you any problems with your hearing.

These types of drugs are very commonly used in developing countries. In the US, they’re used in patients with cystic brosis, lung infections, and tuberculosis. They’re also commonly used to treat premature infants. And cystic brosis patients and premature infants have been found to have a higher rate of hearing loss than the rest of them. Is that because of the drugs they take? In part, it probably is. We really want to know how that happens.

The other question that we’re studying is how sh, frogs, and birds can regenerate their hearing because mammals cannot do that. We’re specically trying to understand how changes in amino acids within proteins could inuence the function of that protein. That could then lead to a dierence in whether or not those cells the protein is in can regenerate.

CB: What is the most interesting thing you’ve come across in your research so far?

AC: I think one of the most interesting things is that dierent drugs damage hearing in dierent ways. Chemotherapy drugs damage hearing in dierent ways from antibiotics. Even antibiotics that are in the same class of antibiotics can damage hearing in dierent ways. We need to better customize therapies to each potential type of hearing damage.

CB: What is your favorite part of your job?

AC: There are a couple of things I love about my job. First, I love working with students in the lab, whether that’s graduate students or undergraduates or high school interns. Seeing them develop as scientists and having them come to me with ideas is great because I love seeing students succeed.

The other thing--most scientists will say this--is getting to be the rst to learn something. For me, uorescent microscopy, getting to look through the microscope at beautifully colored, uorescent samples, is just awesome.

CB: Have you faced any obstacles in the research you’re doing?

AC: Absolutely! One big one that comes to mind is from when I was a postdoctoral researcher at Queens University in Canada. That was my only foray out of hearing and into vision. We were trying to understand a shift in the vision of rainbow trout, which was a ton of fun. The shift is when they go from sh that are swimming around in freshwater to when they’re –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– 33

ready to head out into saltwater. We wanted to study the changes in the retina that happened during that time. This was something that the lab had done for many years, but the lab had just moved to a new university, and I had just joined it, so I was going to try it for the rst time. For the rst eight weeks, I came in seven days a week to work on this experiment. Then, at the end of the experiment, we looked at the shes’ retinas and saw that nothing happened. We did some more troubleshooting, and it turned out that the retina had changed just as we expected, but our detection method wasn't picking it up. That was eight weeks of seven days a week and then what looked like nothing. Then, there was another month of troubleshooting. It was denitely a big challenge, and it was a very frustrating point.

CB: Why do you think people should really pay attention to the research that you’re doing?

AC: First part, I think, is because they should care about their hearing. How many people do you know that have walked out of a concert with their ears ringing? How many people have you seen that turn up their music in their earbuds so loud that you can hear it across the room? People willfully damage their hearing all the time. Without protecting our hearing from all the things we are around, we’re going to lose our hearing very quickly. We all know older relatives that have trouble hearing and that are socially isolated because they can’t communicate in conversations, and they don’t know what’s going on. It’s a challenge. We really lose our connections to the people around us when we’re not able to hear well. That’s to me why people should care about hearing in general. Our research and the research of my colleagues is important because we’re trying to nd ways to prevent hearing loss from happening or to regenerate hearing after it’s been lost so that we’re not socially isolated and so people can hear and enjoy conversations with friends and family.

CB: I volunteer at an Alzheimer’s special care center, and many of the residents there have severe hearing loss. Like you said, they get to the point where they are frustrated because they can’t hear what we’re telling them. Is there a possibility of doing research with sh and neurodegenerative diseases?

AC: To a certain degree. Because sh are so good at regenerating, they don’t show a lot of the signs of neurodegenerative disease like humans and other mammals do. That’s because sh can continue to make new neurons in dierent regions of the brain, of the ear, of the retina, of the spinal cord, etc. They have really remarkable regenerative capacities! But one thing we can do in the sh is mutating genes. Then, if that leads to their loss of the ability to regenerate, we can conclude that the gene is really important for degeneration. Then, we can maybe nd a way to turn that gene on in humans and see if we can spark regeneration. One of my former grad students studied ALS in zebrash. So, there are denitely ways to study neurodegenerative disease in sh.

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CB: Do you have any advice for students interested in neuroscience?

AC: Some advice, in general, is to do what you love! For neuroscience, it’s really great to get some research experience. Volunteer in a research lab, and start when you’re in high school. If you’re at a school that has neuroscience research, look into summer programs. If you join at least one, you can really get that directed research time. You don’t know if you will like that type of research until you try it. Talk to people in careers that you like and nd out more about those careers. Have the kind of balance you want.

References

[1] Con, Allison. (undated). Con Lab Research. [3] Brogan, Jacob. (13/07/2017). Photograph of Zebrash. https://labs.wsu.edu/allison-con/. Retrieved: 04/07/2018. https://www.smithsonianmag.com/smithsonian-institution/cool-n ew-way-freeze-unfreeze-zebrash-embryos-gold-nanotechnology-la sers-180964046/. Retrieved: 04/07/2018. [2] Malewar, Amit. (12/02/2018). Dr. Allison Con Portrait. https://www.techexplorist.com/salmon-face-double-whamm y-toxic-stormwater/11682/. Retrieved: 04/07/2018.

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–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Contributors Page

We could not have made this issue of the IYNA Journal possible without the following people:

IYNA EDITING TEAM:

Editor-In-Chief: Sojas Wagle

Head of Assembly: Christine Zhou

Senior Editors: Anita Singh, Miruna-Elena Vlad, and Robert Morgan

Junior Editors: Aayush Setty, Ansh Verma, Anushka Sarda, Brittany Smale, Joshua Woo, Karina Duy, Natalia Natalia Velasco Gutierrez, Pavan Gudoor, Sanchit Toor, Scott Massey, Stephen Bello, Sulekha Said, Suman Gunin, Vilena Lee

CONTRIBUTING AUTHORS:

Featured Writers: Khayla Black, Vilena Lee

Writers: Kimaya Gadre, Sarah Shirley, Tobey Le, Dharshan Varia, Chinmayi Balusu, Geetanjali Rastogi

IYNA BOARD OF DIRECTORS:

Chief Executive Ocer: Alexander Skvortsov

Board Chair: Jacob Umans

Board Vice-Chair: Daniel Lucas

Board Members: Aayush Setty (Secretary), Onur Tanglay (Treasurer), Sojas Wagle, Yasmeen Hmaidan, Julia Shi, Mallika Pajjuri, Kyle Ryan