How do we form a mind?

Question Proposal: Lars Š. Laichter

Faculty Mentor: Megan J. Bulloch

Faculty Advisor: Darcy K. Otto



    A Question proposal serves as a guiding document for a student’s undergraduate studies at Quest University Canada. Students write their Question proposal as a part of their Question block which concludes the Foundation Program. The goal of the Question proposal is to introduce both academic and personal motivations for pursuing a given Question. It includes an academic statement, a personal statement, as well as a selection of courses, Touchstones, and experiential learning ideas that will allow the student to pursue their Question. Moreover, the Question proposal helps students to identify an appropriate faculty mentor. The Question proposal then also serves as the focal point for an ongoing conversation between student and mentor over the next two years and for the student’s design and implementation of a Keystone project. Although students are not expected to answer their Question definitively, the Question proposal offers each student the opportunity to design a self-guided education and to craft a response to their Question.

Academic Statement

    Nothing other than the mind is so inevitably fundamental and utterly familiar, yet so dizzily enigmatic. René Descartes (1641) illustrates the fundamental role of the mind in our experience by arguing that “I am, I exist, is necessarily true each time that I pronounce it, or that I mentally conceive it”. In this famous argument, Descartes suggests that the only thing that one can be ever certain about is the existence of the mind. Hence, this argument suggests that if one wants to fully understand anything else, one must first understand the mind. In addition, Searle (2015) argues that the mind is a familiar experience to each one of us by claiming that “the operation of mind–conscious and unconscious, free and unfree, in perception, action, and thought, in feeling, emotions, reflection, and memory, and all of its other features–is not so much an aspect of our life, but in a sense, it is our life” (p.6).  Searle suggests that after all, it is only my mind that I experience as my life. Paradoxically, although all of my life is an experience of my mind, I have a limited understanding of the nature of the mind. David Chalmers (2010) argues that problem is much greater than only our individual understanding of our experience by claiming that “there is nothing that we know more intimately than conscious experience, but there is nothing that is harder to explain”. Although the conscious experience is only an element of the mind, the mind as a whole is one of the most puzzling phenomena that we know of and it might be even a phenomenon that we are inherently unable to understand. Nonetheless, the mind is an imminent component of my life and every one of my experiences, as well as a component that appears to be fundamental to many fields of human inquiry and understanding reality as a whole. Given these major implications, I propose my Question: “How do we form a mind?”.

    I shall begin by defining each one of the individual terms that constitute my Question. How is an interrogative pronoun that allows me to ask for a general method or an explanation of causal relationships. Do is an auxiliary verb referring to a general tendency in simple present tense and an action that is factual and repeating. We assumes that other organisms, other than myself, do have a mind and also acknowledges that an understanding of the mind is a collective pursuit which is unlikely to happen in isolation. The verb form allows for enough ambiguity for me to study human and non-human minds, as well as artificially constructed minds. The Oxford dictionary defines the verb form as “bring together parts or combine to create”, but also as “gradually appear or develop” (Oxford University Press, 2017). Hence, the use of the word how allows me to study both how the phenomenon of a mind appears in nature, but also how we can use an understanding of such a phenomenon to artificially replicate it. The use of a instead of the allows me to account for other than human minds, as the mind is often being used to refer only to the human mind. Furthermore, such a formulation will allow me to question the concept of a mind in general.

    Finally, I shall attempt to define the word mind. The Oxford dictionary defines the mind as “the element of a person that enables them to be aware of the world and their experiences, to think, and to feel; the faculty of consciousness and thought” (Oxford University Press, 2017) Firstly, it is important to recognize that the attempt of defining the mind is inherently circular, as it is after all the mind that we are using to come up with the definition of the mind itself. Secondly, the question of a definition of the word “mind” is a matter of ongoing discussion across various disciplines. Hence, given the lack of consensus on the definition of the word mind, I will provide an overview of the most prominent historical conceptions of the mind.

    In philosophy, the specific discipline that studies the mind is called the philosophy of mind. The two major streams in philosophy of mind are dualism and monism. Most of other theories of mind then stems from these two streams. The discussion about what constitutes a mind dates back to ancient Greeks. For example, Aristotle describes mind as “the part of the soul by which it knows and understands” (Smith, 2009). He also includes pain, perception, action and related phenomena to be neither mental not physical. Aristotle was one of the first philosophers to criticize dualism that was prevalent in Plato’s academy (Jaworski, 2011, p.62).

    The dualistic approach to mind encompasses several theories, but they all agree that “the essential nature of conscious intelligence resides in something non physical” (Churchland, 1999). The theory was first formally introduced by the 17th century French philosopher René Descartes. John Searle (2005) even claims that “the philosophy of mind in the modern era effectively begins with the work of René Descartes” (p.9). Descartes argues that “the human mind inasmuch as it is a thinking thing, and not extended in length, width and depth, nor participating in anything pertaining to body, is incomparably more distinct than is the idea of any corporeal thing” (Descartes, 1641). In other words, the mind is a non-material thing that is independent of the body, however, one cannot exist without the other. Descartes also attributes to the mind properties, such as directly known, free, invisible, indivisible, and indestructible which can further shine light on what the mind might be (Descartes, 1641). In addition, some of the major problems of the mind were introduced by René Descartes. These include for example the mind-body problems and the problems of other minds. The mind-body problem arises when we try to understand how thought, feeling, perception, action, and other mental phenomena are related to events in the human nervous system. The problem of other minds arises from a tension between our objective, third person knowledge of human behaviour, and our apparently subjective, first-person knowledge of our own conscious states (Jaworski, 2011, p.17). Both of these problems are among many problems raised by Descartes that continue to puzzle philosophers and scientists.

    To the contrary, the fundamental assumption of monism is that the mind can be explained in terms of a single reality substance (Jaworski, 2011). Some theories of monism are significantly motivated by the hope that the physical sciences could offer a theory of everything and that the mind can be also explained in terms of first principles of the physical sciences (Nagel, 2012). Despite the popularity of this view among contemporary scientists and philosophers, the monist account of the mind remains contagious. For example, Thomas Nagel criticizes this approach by claiming that even if we are able to determine the exact mechanism that gives rise to consciousness, we will never be able to know what is it like to be another organism (Nagel, 1979). Furthermore, as Turing’s proof of undecidability of the Entscheidungsproblem suggests, the mind does not appear to be reducible to first principles, as long as these principles are defined in first order logic (Turing, 1960). These problems of the reductionist monist perspective gave rise to a theory called functionalism. One of the foremost advocates of the functionalist theory was Jerry Fodor with his modularity theory. Fodor proposes that the mind is structured in modules that account for different faculties of the mind (Fodor, 1983). His account is a foundation for the functionalist account of the mind that gave rise to modern cognitive science.

    There are also other non-standard conceptions of the mind. One of the non-standard conceptions of the mind is the extended mind thesis. The extended mind thesis proposes that “cognitive processes may at time extend to the environment surrounding the organism” (Clark, 2007). Clark argues that the “extended mind theory holds that even quite familiar human mental states [...] can be realized, in part, by structures and processes located outside the human head” (Clark, 2011, p.76). In other words, according to this theory, the human mind might not only be encompassed by our conscious experience but also include processes and structures that our body finds itself in, such as our tools and devices. Although this theory promises to address some of the inconsistencies of the previously mentioned theories, it does not currently possess the wealth of empirical backing in comparison to some of the more widely accepted theories. The extended mind thesis has been gaining momentum in the past decades and promises to address some of the problems that have been faced by the standard theories of mind (Clark, 1999).

    It has not been only philosophers that have attempted to understand the nature of the mind. It is also empirical evidence from psychology and neuroscience that maintains its prominent position in the endeavour to understand the mind. Although it is challenging to make the judgment about which empirical evidence contributes to the understanding of the mind and which does not, it is important that theory of mind considers the research that is being done in those disciplines to keep the theories it works with grounded in evidence. For example, it was the research in schemas and scripts, mental imagery, analogical thinking, case-based reasoning that gave rise to increased utilization of cognitive modeling in cognitive science (Thagard, 2007).

    Cognitive science is a discipline which combines all these previously mentioned disciplines of philosophy and psychology, but also adds computer science, as well as sometimes neuroscience, linguistics, and anthropology. Cognitive science is based on the hypothesis that “thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures” (Thagard, 2007). Hence, the idea of utilising computers run cognitive models to further the understanding of the mind stands at the core of cognitive science.

    Cognitive models in cognitive science are being used to test hypotheses about the mind. Computer science has been tightly connected to our attempts to understand the mind since its inception. One of the first cognitive models was built by Newell and Simon in something they called the “thinking machine”. It was a computer program that could prove theorems in logic based on a few axioms (McClelland, 2009). McClelland argues that models in cognitive science are not meant to capture the process that they are trying to elucidate entirely, but rather “they are explorations of ideas about the nature of cognitive processes. In these explorations, simplification is essential— through simplification, the implications of the central ideas become more transparent” (McClelland, 2009). Therefore, it is not the aim to recreate the mind through a computer model, but rather to use the computer model to understand the mind better. Cognitive modelling will most likely remain at the core of the pursuit of understanding the mind, but as McClelland states, it will possibly require both “continued increases in computing power and fundamental new insights taking our models of the nature of cognition beyond the bounds imposed on it by our current frameworks for thinking and modeling” (McClelland, 2009).

    Having presented various possible definitions of the word mind, I shall clarify the scope of my question. There are two main components to my question. The first component is the study of the previously outlined theoretical conceptions of the mind and their relation to the empirical evidence that is being gathered about the mind. The second component is the study of the potential applications of the understanding of the mind through cognitive modeling. Paul Thagard sums up the relationship between theory and experimental evidence well by claiming that “although theory without experiment is empty, experiment without theory is blind” (Thagard, 2006, p.8). Thagard proposes that one of the best ways of developing theoretical frameworks is indeed by forming and testing computational models intended to be analogous to mental operations. This idea is one of the foundational principles of cognitive science, as the goal in cognitive science is to utilize computational models and psychological experimentation hand-in-hand to shine the light on the nature of the mind from an interdisciplinary perspective. Hence, if I want to be able to effectively study the mind, I must master all the elements that constitute the foundation of cognitive science–philosophy, psychology, and computer science. Therefore, I will study philosophy of mind to gain an understanding of all the wide range of theories of mind. I will study psychology to gain an overview of the wide range of empirical evidence about the mind. And finally, I will also study mathematics and computer science that will allow me to work with and build different computational models to test how the theories of mind fit with the empirical evidence.

    Given these two previously outlined approaches, there are three approaches that I will take while exploring my question: (1) I can explore how minds form in humans and other living organisms, as a source of empirical evidence to inform the theories of mind. (2) I can explore how already existing minds can be formed by utilizing understanding from the various theories of mind. (3) I can explore how other minds, maybe artificial minds, can be formed in a computer through the means of computational modeling. I will not choose only one of these approaches, but I will explore all three of them, as they do depend on each other to form a holistic understanding of the mind. Moreover, taking all three of these approaches will allow me to both evaluate different theories of mind based on empirical evidence, as well as to model the empirical evidence in computational models to support a theory.

    In the beginning, I outlined some of the major reasons to study the mind. However, one might ask why it is worth studying the mind from a perspective of cognitive science with the focus on cognitive modeling. I shall offer a justification that accounts both for the practical, as well as the academic implications of studying this question. Beginning with the practical implications, there are many tasks that humans accomplish on daily a basis, be it solving problems, making decisions, communicating with other people, or learning new concepts. All these processes are within the scope of this question. It is by knowing how we accomplish these tasks that we can see where we do poorly and where do we do well. As Thagard (2006) argues “the main aim of cognitive science is to explain how people accomplish their various kinds of thinking”. I will group the possible applications of this understanding according to the previously mentioned three interpretations of my question.

    Firstly, there are direct applications in psychology and psychiatry to allow us to treat instances of processes or actions where our mind performs suboptimally. For example, cognitive models are being used to predict depression. Specific cognitive biases can be targeted with cognitive interventions such as attention training, in which patients learn to shift attention away from negative material automatically, or interpretation training, in which individuals with depression repeatedly learn to develop less negative and more benign interpretations of ambiguous situations (Disner et al., 2011).

    Secondly, there are applications of understanding these processes in the way we structure interactions between humans. For example, understanding these processes can help educators to deliver content to their students efficiently, inform designers and engineers on how to offer their customers the most intuitive experience, or guide politicians in engaging with the people they represent. In education, cognitive models are being used to improve student achievement at various levels and in a variety of subject-matter areas (Thagard, 2006).

    Thirdly, there are also possible applications in the construction of artificial minds and the research of artificial intelligence. Bach (2009) states that results from AI have brought forth independent fields of research as diverse as computer vision, knowledge management, data mining, data comprehension, and the design of autonomous robots (p. vii). McClelland argues that “one exciting area of future development for cognitive modeling is in the control of situated cognitive agents interacting with other agents and the real world” (McClelland, 2009). Today researchers are already able to use Sony’s ambulatory humanoid robot to explore simplified worlds containing small numbers of high-contrast objects that the agents can learn to approach, avoid, manipulate, and describe to each other in a simplified spoken language (Steels, 2007).

    One could object that there are other methods, such as solely psychology or neuroscience, that could offer us answers about the nature of the mind. Nevertheless, it is the new unified architecture of how to study the mind in cognitive science that appears to have a promise of offering more answers. As Bach illustrates through an analogy, cognitive scientists are “in a situation similar to that of the cartographers who set out to draw the first map of the world, based on the reports of traders and explorers returning from expeditions into uncharted waters and journeys to unknown coasts” (Bach, 2009, p. ix). In other words, cognitive science is in the unique position to be able to synthesise the empirical evidence from psychology and neuroscience to construct new theories and further our understanding of the mind. Therefore, given this new opportunity to study the mind through a different method, this question is addressing a possible gap and opening an opportunity for a generation of new knowledge.

    There are important philosophical implications in pursuing this question. One of the major examples is free will. The study of the mind has the potential illuminate the question whether we possess free will or whether all of our choices are merely caused by the physical processes in the brain. Hence, another example is the implication in ethics. If we are indeed only products of the physical processes in our mind, there are major ethical implications on how humans should treat each other or how we should treat other beings (Carruthers, 1989). For example, if animals are only non-conscious automata, we do not need to take into account their pain, as they would have in fact no experience of it. Another example of a major question that can be informed by the study of the mind is innateness. Innateness is the question about the extent to which knowledge is innate or acquired which is also being referred as the question of nature versus nurture (Thagard, 1996). These are only a few out of many examples in philosophy that can be informed by the study of the mind.

    To conclude, I have shown that studying the mind has a wide range of applications both in various fields of intellectual inquiry, as well as practical applications. Given all the gaps in knowledge, there are also many opportunities for further study, development, or research. I hope that with this argument I have shown that the mind is not only a field with potentially major implication on various corners of society, but also that it is an exciting field with a range of intellectually stimulating questions. Finally, I shall use my reasoning to outline what courses, Touchstones, and experiential learning ideas will allow me to pursue my Question further.


Course plan





Course schedule

Block 1 Block 2 Block 3 Block 4
Fall 2015 Cornerstone Rhetoric Culture: Fabric of Reality Political Economy
Spring 2016 Text: Utopias and Dystopias Computer Programming Evolution What is life?
Summer 2016 Mathematical Problem-Solving Our Chemical World
Fall 2016 Biodiversity of BC Global Perspectives Algorithm Analysis and Design Logic & Metalogic
Spring 2017 Cognition Animals & Ethics Question Politics of Cyberspace
Summer 2017 Earth, Oceans, and Space Linear Algebra
Spring 2018 Abstract Algebra Multivariable Calculus Democracy and Justice Scholarship
Summer 2018 Experiential Learning
Fall 2018 Language Independent Study Cognitive Development Another Independent Study? Keystone


Experiential learning

Option 1: Research Lab Intern

    One of the options for my experiential learning is to intern in a cognitive science research lab. I must consider multiple research labs, as placements in research labs are highly competitive and would likely have to outcompete applicants from that given university. One option how to get a placement in a research lab is to contact labs directly and inquire about the possibility of a placement. Alternatively, I could inquire with my mentor if she has any connections that might help in searching for a possible placement. If I would like a placement for the summer in 2018, I would have to start contacting various labs at least in January 2018. Informal networking might be helpful to gain access to such opportunities too. This might include attending meetups, presentations, or conferences related to cognitive science.

    While interning in a research lab, I would be able to improve my research skills and gain a first-hand perspective on what it means to be a cognitive scientist. It could be either the results of my work that I could present to my mentor to show progress on these learning objectives, or journal report reflecting on my progress during the internship. Here are some of the labs that I could potentially contact in order to apply for a placement:

Option 2: Start-up Intern    

    A second potential avenue for my experiential learning is to acquire an internship in a startup engaged with topics of cognitive science or philosophy of mind. These might include startups primarily in the area of cognitive modeling or artificial intelligence. Although startups are often short of funds, they are mostly in need of more people, thus it is potentially easier to receive an internship in a startup rather than in an established company. Given my prior experience in design and programming, I have some of the skills that are needed in the startup environment. Having worked on my own during my gap year, I have a relatively solid network of people in the industry, including major startup hubs, such as Amsterdam, Berlin, or San Francisco. Therefore, I could easily inquire in my network on potential jobs that do have a connection to cognitive science.

    Some of the learning objectives that I could consider in a case of such scenario might be improvement of my programming, design and analytical skills. I could either present to my mentor the work that I will have done during such an internship or I could keep a journal on my learning progress while working. If I would want to do my experiential learning in the summer 2018, I will have to reach out to various startups at least by January 2018. Here are some of the startups that I might consider interning for:



    There are two possible avenues for my keystone, as either, I can program my cognitive model, or I can write a theoretical paper on one of the philosophical problems in philosophy of mind. The choice between one or the other will primarily depend on what kind of program I will decide to pursue after Quest. If I decide to go into cognitive science, then programming a cognitive model would be probably a better application. On the other hand, if I decide to continue my studies in philosophy of mind, a paper on one of the problems in philosophy of mind would be probably better for my application. Of course, the best would be if I could do both, as I find both interesting. My decision between these two options will be primarily informed by my readings during the summer and the courses that I plan to take next year.

    Some of my ideas, if were to program a cognitive model, include options such as building a model based on the theory of embodied cognition. The theory of embodied cognition seems to provide an interesting alternative to the more traditional theories of cognition, as well as address various shortcomings of contemporary cognitive science, such as the role of emotions or the situatedness of the body. In this context, I would be interested in exploring the possible avenues for embodied cognition to be incorporated in cognitive models, especially in the context of the control of situated cognitive agents interacting with other agents and the real world.


Personal Statement    

    I have likely had to face various questions concerning the mind since an early age. However, I began to puzzle myself with questions about the mind explicitly after one of my close family members committed suicide, following many years of problems with bipolar disorder. Thus, it was a deformity of the mind that made me wonder about what forms the mind in the first place. This wonder has led me to curious places ever since.

    Initially, it led me to explore the question of whether one could form a mind in a computer. After having tried to design a robot that could aid with the interaction with such a mind, I proceeded to entertain the idea of one forming a collective mind by improving the interaction between already existing human minds. Undoubtedly these were immature ideas, yet they inspired me to take a gap year and to explore them further. During my gap year, I ended up developing a voice-based app called Noema, that was meant to enable people to communicate with strangers from around the world and discover new thoughts and ideas. Nonetheless, I decided to abandon these projects and to pursue my studies at Quest.

    Courses such as Logic & Metalogic, Cognition, and Animals & Ethics exposed me to some of the difficult questions concerning the mind and convinced me that not only do I find these questions deeply meaningful, but that I also want to further pursue them in an academic setting. Moreover, the combination of philosophy, psychology and computer science, which together form the foundation of cognitive science, seems to be suiting both my intellectual curiosities and practical talents. I hope that this question will continue to take me to curious places and possibly will enable me to pursue a program in cognitive science or philosophy of mind after finishing my studies at Quest.


  1. Bach, J. (2009). Principles of synthetic intelligence: PSI, an architecture of motivated cognition. Oxford: Oxford University Press.
  2. Block, N. (n.d.). Introduction: What Is Functionalism? The Language and Thought Series. doi:10.4159/harvard.9780674594623.c17
  3. Carruthers, P. (1989). Brute Experience. The Journal of Philosophy,86(5), 258. doi:10.2307/2027110
  4. Carruthers, P. (2004). The nature of the mind: an introduction. New York: Routledge.
  5. Chalmers, D. J. (2010). Facing Up to the Problem of Consciousness. The Character of Consciousness, 3-34. doi:10.1093/acprof:oso/9780195311105.003.0001
  6. Churchland, P. M. (1999). Matter and Consciousness - Revised Edition. MIT Press.
  7. Clark, A. (1999). An embodied cognitive science? Trends in Cognitive Sciences,3(9), 345-351. doi:10.1016/s1364-6613(99)01361-3
  8. Clark, A. (2007). Curing Cognitive Hiccups. Journal of Philosophy,104(4), 163-192. doi:10.5840/jphil2007104426
  9. Clark, A. (2011). Supersizing the mind: embodiment, action, and cognitive extension. Oxford: Oxford University Press.
  10. Descartes, R. (1641). Meditations on First Philosophy. Descartes: Meditations on First Philosophy, 1-11. doi:10.1017/cbo9780511805028.006
  11. Disner, S. G., Beevers, C. G., Haigh, E. A., & Beck, A. T. (2011). Neural mechanisms of the cognitive model of depression. Nature Reviews Neuroscience,12(8), 467-477. doi:10.1038/nrn3027
  12. Fodor, J. A. (1983). The Modularity of Mind. Cambridge, MA: The MIT Press.
  13. Jaworski, W. (2011). Philosophy of mind: a comprehensive introduction. Chichester, UK: Wiley-Blackwell.
  14. McClelland, J. L. (2009). The Place of Modeling in Cognitive Science. Topics in Cognitive Science, 1(1), 11-38. doi:10.1111/j.1756-8765.2008.01003.x
  15. Nagel, T. (1979). What Is It Like to Be a Bat? The Language and Thought Series. doi:10.4159/harvard.9780674594623.c1
  16. Nagel, T. (2012). Mind and cosmos why the materialist neo-Darwinian conception of nature is almost certainly false. New York: Oxford University Press.
  17. Oxford University Press. (2017). Definition of mind in English. Retrieved March 22, 2017, from
  18. Oxford University Press. (2017). Definition of mind in English. Retrieved March 22, 2017, from
  19. Searle, J. R. (2005). Mind: a brief introduction. New York: Oxford University Press.
  20. Smith, J. A. (2009). The Internet Classics Archive | On the Soul by Aristotle. Retrieved March 23, 2017, from
  21. Steels, L. (2007). Fifty Years of AI: From Symbols to Embodiment - and Back. 50 Years of Artificial Intelligence Lecture Notes in Computer Science, 18-28. doi:10.1007/978-3-540-77296-5_3
  22. Thagard, P. (1996, September 23). Cognitive Science. Retrieved April 04, 2017, from
  23. Thagard, P. (2006). Mind: introduction to cognitive science. New Delhi: Prentice-Hall of India.
  24. Thagard, P. (2007, April 30). Cognitive Science. Retrieved March 24, 2017, from
  25. Turing, A. (1960). On Computable Numbers, with an Application to the Entscheidungsproblem. Annual Review in Automatic Programming, 230-264. doi:10.1016/b978-0-08-009217-1.50024-4