A Prelude to Modular Theory Few can contest the complicated and interdisci- plinary origins of neuroscientific study, as its precise date of birth is obscure. However, it is important to place the first true and deliberate neuroscience studies in proper histori- cal context so we can fully appreciate and understand why topics were studied through the lens of modular theory. Ancient Egyptians considered the brain and its organic projections to be little more than waste, instead believing that the true “seat of the soul” was the heart (Chudler, n.d.). This view was replicated in early Greek and biblical texts but represented the consolidation of personality and human character into physiological terms. Later, Hippocrates and his followers rebuked this dogma in early physiology, instead arguing that the brain was the major control center for the body and possessed three ventricles, each of which was responsible for a different mental faculty: imagination, reason, and memory (Chudler, n.d.). This view was support- ed by the Greek physician Galen who wrote extensively on the subject and had a profound influence on Enlightenment philosophers such as Rene Descartes (Chudler, n.d.). Hippocrates, Galen, and Descartes’ collective writ- ings emphasized an increas- ingly compartmentalized view of brain structure and function, a sentiment that came to a head in the early 19th century under the directorship of the German physiologist Franz Joseph Gall, the founder of the study of phrenology (Fodor, 1983). Phrenology borrowed major tenets of previous neurophysiological literature such as continu- ing to support the notion that the brain was the principal organ of the mind. Gall took those previous ideas to new maxims, claiming that the brain represented a collection of precisely localized cerebral organs with specific functions (Figure 1). The strength and proficiency of those particular functions, he argued, were proportional to the relative sizes and geometries of their respective skull regions. Many would correctly conclude this understand- ing of neurophysiology to be akin to pseudoscience, but the dangerous influence phrenology has had on research in neuroscience must not be understated. The writings and lectures of Gall, his collaborators, and his students spread throughout the English-speaking world during the 19th century and fomented a number of debates about the methods employed to justify the major principles of phre- nology (Yildirim & Sarikcioglu, 2004). Physiologist Jean Pierre Flourens performed experimental brain excisions on pigeons and observed their consequential behavior to demonstrate that the defined brain regions in phrenology had little experi- mental backing. These ablations, however, caused varied deficiencies and behavioral abnormalities suggesting that some interplay did still exist between brain regions and behavior (Yildirim & Sarikcioglu, 2004). An avalanche of research soon followed, characterizing and qualifying these interactions, along with the functions of a number of other brain and nerve components (Figure 2). Were it not for the early writings and claims of phrenology, the brain might have not been drawn into so many distinct components over the next two centuries. Modular Theory Comes Under Scrutiny Significant progress has been made over the last several decades in analyzing and characterizing brain regions and tissues. Our predecessor neurophysiologists of the late 1700s and 1800s lacked the sophisticated imaging technology we use today. Our imaging techniques provide a far more nuanced view of the brain, permitting us to see individual cells with profound resolution as seen in the Golgi stain- ing technique (Finger, 2004). Golgi staining, developed by Camillo Golgi in 1873, entails the perfusing of silver ni- trate into the cell bodies of neurons, the functional unit Outcomes in Neuroscience Education: Modular Theory and Network Theory Thomas Romanchek Figure 1: Phrenology chart [jpg]. (1920). Retrieved from https:// www.sciencephoto.com/media/1002821/view/phrenology-chart Figure 2: Blausen.com staff (2014). Medical gallery of Blausen Medical 2014 [png]. Retrieved from https://en.wikipedia.org/wiki/Human_brain#/media/File:Blausen_0102_ Brain_Motor&Sensory_(flipped).png Figure 3: MethoxyRoxy (2005). Pyramidal hippocampal neuron [jpg]. Retrieved from https:// commons.wikimedia.org/wiki/File:Pyramidal_hippocampal_neuron_40x.jpg 1 Brain Matters Volume 2 of the nervous system. The resulting stains depict darkened cell bodies and axons, the cellular projections that neurons use to communicate with one another (Figure 3). This advent in imaging technology allowed scientists to observe the actual connections and highways of communication between distant regions within the nervous system (Finger, 2004). Modular theory was beginning to be forced on the defense for the first time since its birth two centuries prior. Cell imaging had its uses but had fairly limited applications when it came to in-vivo study of the brain and its operations. Cell and tissue isolation required the sacrifice of animal subjects and the collection of brain matter from cadavers. The first in-vivo studies of brain function and organization came about as the result of the invention of the x-ray in 1895 by Wilhelm Konrad Roentgen. The first images from this technology gave researchers a valuable opportunity to observe naturally-occurring brain deteri- oration in living human subjects and to relate the damage location and intensity with the behaviors and actions the subjects expressed (Finger, 2004). Early work demonstrated the lack of uniformity in brain tissue between humans. Re- gions thought to be related to language comprehension and speech production were found to differ in size and location between subjects. Furthermore, the degree of gyration of those and other brain regions was unique for everyone who was imaged (Triarhou, 2017). Overt dissimilarities in brain appearance began to give way to mounting criticism of the well-defined module mold of brain organization. Both cell and brain imaging had important im- plications in research, but limited potential because each perspective provided only a snapshot of activity at a single given moment. It was not until the invention and im- plementation of imaging and even neurostimulator technologies that such a feat was possible. Positron emission tomog- raphy (PET) and magnetic resonance imaging (Figure 4) allowed scientists to observe the brain in action and directly measure the activ- ity of brain regions through the circula- tion and exchange of blood and oxygen. These were com- plemented with experimental chemical stimulation, light stimulation through optogenetics, and Transcranial Mag- netic Stimulation (Figure 5) to directly test relationships of stimulation and inhibition with brain activity (Badcock et al., 2019). These technologies revealed the limited impor- tance of clusters of cells and tissues in action execution, and the greater relevance of their overarching and interconnected communi- cation networks. However, a substantial disconnect still exists between what research has managed to reveal about the merits of network theory and what is being actively taught in classrooms. ReferencesReferences Badcock, P. B., Friston, K. J., Ramstead, M. J. D., Ploeger, Badcock, P. B., Friston, K. J., Ramstead, M. J. D., Ploeger, A., & Hohwy, J. (2019, May 21). The hierarchically mechanistic mind: an evolu-A., & Hohwy, J. (2019, May 21). The hierarchically mechanistic mind: an evolu- tionary systems theory of the human brain, cognition, and behavior. Retrieved tionary systems theory of the human brain, cognition, and behavior. Retrieved from https://doi.org/10.3758/s13415-019-00721-3from https://doi.org/10.3758/s13415-019-00721-3 Bassett, D. S., & Sporns, O. (2017). Network neuroscience. Nature neuroscience, Bassett, D. S., & Sporns, O. (2017). Network neuroscience. Nature neuroscience, 20(3), 353–364. doi:10.1038/nn.450220(3), 353–364. doi:10.1038/nn.4502 Blackmore, D.G. (2013). Massive Modularity: Why it is Wrong, and What it Can Blackmore, D.G. (2013). Massive Modularity: Why it is Wrong, and What it Can Teach us Anyway.Teach us Anyway. Chudler, E. H. (n.d.). Milestones in Neuroscience Research. Retrieved from Chudler, E. H. (n.d.). Milestones in Neuroscience Research. Retrieved from https://faculty.washington.edu/chudler/hist.htmlhttps://faculty.washington.edu/chudler/hist.html Finger, Stanley (2004). Minds Behind the Brain: A History of the Pioneers Finger, Stanley (2004). Minds Behind the Brain: A History of the Pioneers and Their Discoveries. New York: Oxford University Press. p. 29. ISBN 978-and Their Discoveries. New York: Oxford University Press. p. 29. ISBN 978- 01951818210195181821 Fodor, J. A. (1983). The Modularity of mind. Cambridge, MA: The MIT Press.Fodor, J. A. (1983). The Modularity of mind. Cambridge, MA: The MIT Press. National Institutes of Health. (2018, November 2). NIH greatly expands invest-National Institutes of Health. (2018, November 2). NIH greatly expands invest- ment in BRAIN Initiative. Retrieved from https://www.nih.gov/news-events/ment in BRAIN Initiative. Retrieved from https://www.nih.gov/news-events/ news-releases/nih-greatly-expands-investment-brain-initiative.news-releases/nih-greatly-expands-investment-brain-initiative. Sporns, O., & Betzel, Sporns, O., & Betzel, R. F. (2016). Modular Brain Networks. Annual review of psychology, 67, 613–640. doi:10.1146/annurev-psych-122414-033634 Triarhou L. C. (2017). The Comparative Neurology of Neocortical Gyration and the Quest for Functional Specialization. Frontiers in systems neuroscience, 11, 96. doi:10.3389/fnsys.2017.00096 White House Office of the Press Secretary. (2013, April 2). Fact Sheet: BRAIN Initiative. Retrieved from https://obamawhitehouse.archives.gov/the-press-of- fice/2013/04/02/fact-sheet-brain-initiative Yildirim, F. B., & Sarikcioglu, L. (2007). Marie Jean Pierre Flourens (1794 1867): an extraordinary scientist of his time. Journal of neurology, neurosurgery, and psychiatry, 78(8), 852. doi:10.1136/jnnp.2007.118380 Figure 4: Leblanc, R. (2009). Sagittal T1 Midline MRI Scan of Reigh’s Brain [jpg]. Retrieved from https://www.flickr.com/photos/reighleblanc/3854685038. Figure 5: US National Institute on Aging, Alzheimer’s Disease Education and Referral Center (2008). PET scan of a normal human brain [jpg]. Retrieved from https://commons.wikimedia.org/wiki/ File:PET_Normal_brain.jpg. Brain Matters Volume 2 2