Go to main content

Philosophy of Mind: Neural Networks, Information Processing, and AI

Philosophy of Mind (16:730:575)
Spring 2019, Thursdays, 9:50am-12:50pm
Philosophy Seminar Room, 106 Somerset St.
Susanna Schellenberg
Office hours by appointment

Course Description

This course focuses on mental representations and the neural base, more specifically on neural networks, information processing, and AI. Topics include:

  1. Explanatory strategies in neuroscience (with a particular focus on the neuroscience of vision and neurolinguistics)
  2. The relationship between neuroscience research and higher-level disciplines such as psychology
  3. The role representations play in cognitive, computational, and cellular neuroscience
  4. The relationship between mental states and the chemical or electrical activity of the brain

The goal is for students to be able to reflect critically on research in neuroscience from a philosophical perspective. This requires not just learning what particular neuroscientists or philosophers have said about neuroscience inquiry, but also formulating, testing, and defending one’s own views.


Reading Requirement: Each student must read the assigned reading before class. There will be reading assignments for each class meeting. The reading assignments will be made available either in a dropbox folder or via links in the schedule below.

  • Questions Requirement: Each student must submit two questions on the reading for each class meeting. Questions must be submitted by email to schellenbergteaching@gmail.com by 10pm on the day before the relevant class meeting. The questions will determine 20% of your grade.
  • Abstract Requirement: A 200 word abstract for your seminar paper. The abstract will present the main idea of your paper and explain why that idea is interesting. It should “sell” the paper to the reader. Each abstract will be read and discussed in class. The abstract will determine 10% of your grade. The abstract is due March 7.
  • Paper Outline Requirement: A 1-page outline of your seminar paper. The outline should list each section title and subsection title of your paper along with a 1-2 sentence description of what will happen in that section. The outline will determine 10% of your grade. The paper outline is due April 4.
  • Handout Requirement: Each student will make a 1-page handout that they will distribute before their presentation. The handout will contain the thesis of the seminar paper, the main question addressed as well as the key ideas and arguments of the seminar paper. The handout will determine 10% of your grade. The handout is due right before the presentation of the paper.
  • Presentation Requirement: Each student will present their seminar paper at the seminar workshop. The presentation will determine 20% of your grade.
  • Paper Requirement: One seminar paper (about 15-pages). This is the same paper that you will have presented. The paper will determine 30% of your grade. Papers should be typed, double-spaced, 12pt font, 1” margins and submitted as word-documents by email attachment to schellenbergteaching@gmail.com. Due May 15.
  • All written work (questions, abstract, outline, handout, paper) should be sent to schellenbergteaching@gmail.com.

Reading Material

  • All reading material will be made available either on this page or in a dropbox folder the link to which will be provided in class.
  • If you want to buy a book, you could buy one of these:
  • Nicholas Shea, Representation in Cognitive Science, Oxford: Oxford University Press 2018.
  • The Cambridge Handbook of Cognitive Science, edited by Keith Frankish and William Ramsey (2012, Cambridge University Press)
  • Bechtel, W., Mandik, P., Mundale, J., and Stufflebeam, R. S. (eds.) (2001). Philosophy and the Neurosciences: A Reader. Oxford: Blackwell


Office Hours

If you have questions, concerns, or just want to talk about the class material, please don’t hesitate to contact me to make an appointment.


You are encouraged to form a reading group to discuss the reading.


Introduction and Background: Functionalism, Materialism, Physicalism


No class or class on 1/29

Philosophical Foundations of Neuroscience

Coltheart, M. (2001). Assumptions and methods in cognitive neuropsychology. In B. Rapp (ed.), The Handbook of Cognitive Neuropsychology: What Deficits Reveal About the Human Mind (pp. 3-21). Hove: Psychology Press.

Shea, N. (2018): Representation in Cognitive Science, Chapter 1

Further reading:
Abramsen, Adele & Bechtel, William: History and core themes. In Frankish & Ramsey, Ch 1

Bennett, M. and Hacker, P. (2003). Philosophical Foundations of Neuroscience (excerpt). in Neuroscience and Philosophy, ed. Bennett et al, p. 15-33.


Neural Mechanism and Cognition

Mundale, Jennifer: Neuroanatomical Foundations of Cognition: Connecting the Neuronal Level with the Study of Higher Brain Areas

Shea, N. (2018): Representation in Cognitive Science, Chapter 2

Further Reading:
Shea, N. (2013). Neural Mechanisms of Decision-Making and the Personal Level. In ‘Oxford Handbook of Philosophy and Psychiatry’, ed. K. Fulford et al. Oxford: Oxford University Press (pp. 1063-1082).

W.Bechtel, “Cognitive Neuroscience: Relating Neural Mechanisms and Cognition.”


Mental Representation and Functions

Shea, N. (2018): Representation in Cognitive Science, Chapter 3: Functions for Representations

Further reading on mental representations:

Von Eckhardt, Barbara: The representational theory of mind. In Frankish & Ramsey, Ch 2]

David Marr, Vision, General Introduction and Ch. 1.

Zenon Pylyshyn, Things and Places: How the Mind Connects with the World. Ch. 1.

Tyler Burge (2010).  Origins of Objectivity, Oxford University Press, Ch.  8, pp. 291-366.

Frances Egan, “How to Think about Mental Content”, Philosophical Studies, (2014).

Jerry Fodor, “A Theory of Content I”. In A Theory of Content and Other Essays, Ch.  3.

Jerry Fodor, “A Theory of Content II”. In A Theory of Content and Other Essays, Ch. 4.

Hartry Field (1978). “Mental Representation”.

Shea, N. (2013) “Naturalising representational content.” Philosophy Compass 8.5: 496-509.

Causal Theories of Content, Stanford Encyclopedia of Philosophy.

Further reading on functions: see below


Information Processing and Representations

Shea, N. (2018): Representation in Cognitive Science, Chapter 3: Correlational Information

Further Reading

Dennett, D. (1988) “Evolution, Error and Intentionality,” in Y. Wilks and D. Partidge (eds.), Sourcebook on the Foundations of Artificial Intelligence, New Mexico University Press: New Mexico.

Fodor, J. (1990b). “Information and representation.” In Information, Language and Cognition, ed. Philip Hanson. Vancouver: University of British Columbia Press.


Structural Representation

Shea, N. (2018): Representation in Cognitive Science, Chapter 4: Structural Representation

3/7 Abstracts due; discussion of abstracts in class


Fodor and Pylyshyn (1998), “Connectionism and Cognitive Architecture: A Critical Analysis.”

Further Reading:

Mahon, Bradford: Missed Connections: A Connectivity-Constrained Account of the Representation and Organization of Object Concepts

Garson (2015) “Connectionism,” Stanford Encyclopedia of Philosophy.

Geoffrey E. Hinton (1992), “How Neural Networks Learn from Experience.”

Smolensky (1998) “Connectionism, Constituency, and the Language of Thought.”

Stan Franklin (1995), Artificial Minds, Ch. 6: “Connectionism”, Ch. 7: “The Second AI Debate.”

Chalmers (2003) “Why Fodor and Pylyshyn Were Wrong: The Simplest Refutation.”


Neural Mechanisms

Craver, C. (2005). Beyond Reduction: Mechanisms, Multifield Integration and the Unity of Neuroscience, Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2): 373-395.

3/21 spring break


Neural Mechanism and Multiple Realization

Polger, T. (2010). Mechanisms and Explanatory Realization Relations, Synthese, 177(2): 193-212.

Further Reading

Bechtel, W. and Mundale, J. (1999). Multiple Realizability Revisited: Linking Cognitive and Neural States, Philosophy of Science, 66(2): 175-207.

Aizawa, K. and Gillett, C. (2009). The (Multiple) Realization of Psychological and Other Properties in the Sciences, Mind & Language, 24(2): 181-208.

Sullivan, J. (2008). Memory Consolidation, Multiple Realizations, and Modest Reductions, Philosophy of Science, 75(5): 501-513.

4/4 paper outline due; discussion of paper outlines in class

AI and Neuroscience

Demis Hassabis et al. (2017), “Neuroscience-Inspired AI”

Further Reading:

John Krakauer (2017) Neuroscience Needs Behavior correcting reductionist bias.



paper outline due

Jack Copeland (1993), Artificial Intelligence: A Philosophical Introduction, Chs. 1 and 2: “The beginnings of Artificial Intelligence: a historical sketch” and “Some Dazzling Exhibits.”

Margaret Boden (2016), AI: Its Nature and Future, Ch 2: “General Intelligence as the
Holy Grail.

4/18 no class (Pacific APA)


Neural Correlates of Consciousness

Wu, W (2018), Neuroscience of Consciousness, SEP

David Chalmers, What is a Neural Correlate of Consciousness? in Metzinger (ed.), The Neuronal Correlates of Consciousness, MIT, 2000.

Further Reading

Block, Ned. (2005). Two neural correlates of consciousness. Trends in Cognitive Sciences, 9, 46–52.

Crick and Koch: Consciousness and Neuroscience https://academic.oup.com/cercor/article/8/2/97/307049

Gold and Stoljar, A neuron doctrine in the philosophy of neuroscience. Behavioral and Brain Sciences 22(5), 1999, and here. Patricia Churchland, Can Neurobiology Teach Us Anything About Consciousness?

Lau, H, Theoretical motivations for investigating the neural correlates of consciousness, WIREs Cognitive Sciences, 2:1 p.17.

4/30 Tuesday, 1pm, Colloquium Talk by Rosa Cao (Stanford) at RuCCS. All are encouraged (but not required) to attend the talk.

5/2 workshop; keynote speaker: John Morrisson (Columbia)


Related topics not covered in class


Millikan, R. (1989b) “In Defense of Proper Functions.” Philosophy of Sci- ence 56 (2): 288–302

Wright, L., (1973) “Functions,” in The Philosophical Review, 82: 139–168

Cummins, R. (1975) “Functional Analysis.” The Journal of Philosophy 72, no. 20: 741–65;

Neander, K. (1991) “The teleological notion of ‘function.’” Australasian Journal of Philosophy 69.4:  454–468.

Nanay, B. (2010) “A Modal Theory of Function.” The Journal of Philosophy 107.8: 412–431

Price, C. J., and Friston, K. (2005). Functional ontologies for cognition: The systematic definition of structure and function. Cognitive Neuropsychology, 22, 262-275.

Poldrack, R. A., Halchenko, Y., and Hanson, S. J. (2009). Decoding the large-scale structure of brain function by classifying mental states across individuals. Psychological Science, 20, 1364-1372.

Lenartowicz, A., Kalar, D. J., Congdon, E., and Poldrack, R. A. (2010). Towards an ontology of cognitive control. Topics in Cognitive Science, 2, 678-692.

Klein, C. (2012). Cognitive Ontology and Region-versus Network-Oriented Analyses. Philosophy of Science, 79(5), 952-960.

Lindquist, K. A., & Barrett, L. F. (2012). A functional architecture of the human brain: emerging insights from the science of emotion. Trends in cognitive sciences, 16, 533-540. Anderson, M.L. (2015). Mining the brain for a new taxonomy of the mind. Philosophy Compass, 10, 68-77.

Reductionism in Cognitive Neuroscience

Bickle: Reducing mind to molecular pathways: explicating the reductionism implicit in current cellular and molecular neuroscience.

Cognitive Neuropsychology and Double Dissociation

Davies, M. (2010). Double dissociation: Understanding its role in cognitive neuropsychology. Mind & Language, 25, 500-540.

Cognitive Architecture

Thagard, Paul: Cognitive architecture. In Frankish & Ramsey, Ch 3

Further reading

Ned Block, Chapter 4 of The Border between Seeing and Thinking.

What can we Learn from Neuroimaging?

Poldrack, R. A. (2006). Can cognitive processes be inferred from neuroimaging data? Trends in Cognitive Sciences, 10, 59–63.

Hutzler, F. (2014). Reverse inference is not a fallacy per se: Cognitive processes can be inferred from functional imaging data. NeuroImage, 84, 1061-1069.

Integrating Psychology and Neuroscience

Piccinini, G. and Craver, C. (2011). Integrating Psychology and Neuroscience: Functional Analyses as Mechanism Sketches, Synthese, 183(3): 283-311.

Kaplan, D. (2011). Explanation and Description in Computational Neuroscience, Synthese, 183(3): 339-373.

Teleological Accounts, Misrepresentation, and the explanatory power of positing representations

Millikan, R. (1989) “Biosemantics.” Journal of Philosophy 86: 281–297;

Pietroski, P. (1992) “Intentional and teleological error.” Pacific Philosophical Quarterly 73: 267–281.

Karen Neander (2012). “Teleological Theories of Mental Content”, Stanford Encyclopedia of Philosophy.

Further Reading:

Dretske, F. (1986) “Misrepresentation.” In Belief: Form, Content and Function, New York, ed. Radu Bogdan, 17–36. Oxford, UK: Clarendon Press.

Introduction, Chapters 1-2 of Fodor, J. (1987) Psychosemantics: The Problem of Meaning in the Philosophy of Mind. Cambridge, MA: The MIT Press.

Neural Mechanisms and the Personal/Subpersonal Distinction

Colombo, M. (2013). Constitutive Relevance and the Personal/Subpersonal Distinction, Philosophical Psychology, 26(4): 547-570.

Computationalism and Cognitive Neuroscience

Von Eckardt, B. and Poland, J. (2004). Mechanism and Explanation in Cognitive Neuroscience, Philosophy of Science, 71: 972-984.

Egan, F. Function-Theoretic Explanation and Neural Mechanisms. In ‘Integrating Mind and Brain Science: Mechanistic Perspectives and beyond’, ed. D. Kaplan. Oxford University Press.

Laws In the ‘Special Sciences’

Cummins, R. (2000). ‘How Does it Work?’ Versus ‘What Are the Laws?’: Two Conceptions of Psychological Explanation. In ‘Explanation and Cognition’, ed. F. Keil and R. Wilson. Cambridge, MA: MIT Press (117-144).

Intentional Concepts in Cognitive Neuroscience

Pöyhönen, S. (2014). Intentional Concepts in Cognitive Neuroscience, Philosophical Explorations, 17(1): 93-109.


Samuels, Richard. (2004). Innateness in cognitive science. Trends in Cognitive Sciences, 8, 136–141.


Williamson, T. “Can cognition be factorised into internal and external components?” In Robert Stainton, ed. Contemporary Debates in Cognitive Science. Blackwell.

Is there any causal role for externalist mental states?

Burge, T. (1986) “Cartesian error and the objectivity of perception” in P. Pettit and J. McDowell, eds., Subject, Thought and Context. Oxford Univ. Press, Oxford, 117-36. Reprinted in Grimm and Merrill, ed. (1988) Contents of Thought. Univ. of Arizona Press, Tucson, 62-76.

Kim, J. (1982) “Psychophysical supervenience” PS 41, 51-70. Reprinted in Kim (1993) Supervenience and Mind. Cambridge Univ. Press, Cambridge, 175-93.


Fodor, J. (1983) Chapter 4 of Modularity of Mind: An Essay on Faculty Psychology:

Biased Algorithms


Knight, Will: Biased Algorithms are Everywhere, and No One Seems to Care.

Implicit Bias

Tamar Gendler (2011) “On the Epistemic Costs of Implicit Bias” Philosophical Stud- ies, 156:33-63. Student presenter.

Michael Brownstein (2015) “Implicit Bias” Stanford Encyclopedia of Philosophy.


Janet Levin (2013) “Functionalism”, Stanford Encyclopedia of Philosophy.

Block, Troubles with Functionalism, in Minnesota Studies in the Philosophy of Science 9:261325 (1978), and in Readings in the Philosophy of Psychology, Vol. 1, Ned Block (ed.) Harvard, 1980.


Daniel Stoljar (2015) “Physicalism”, Stanford Encyclopedia of Philosophy.


Paul Churchland, Eliminative Materialism and the Propositional Attitudes.