Invited Talk
Workshop: I Can’t Believe It’s Not Better: Understanding Deep Learning Through Empirical Falsification

Lawrence Udeigwe: On the Elements of Theory in Neuroscience.

Lawrence Udeigwe


In science, theories are essential for encapsulating knowledge obtained from data, making predictions, and building models that make simulations and technological applications possible. Neuroscience -- along with cognitive science -- however, is a young field with fewer established theories (than, say, physics). One consequence of this fact is that new practitioners in the field sometimes find it difficult to know what makes a good theory. Moreover, the use of conceptual theories and models in the field has endured some criticisms: theories have low quantitative prediction power; models have weak transparency; etc. Addressing these issues calls for identifying the elements of theory in neuroscience. In this talk I will try to present and discuss, with case studies, the following: (1) taxonomies by which the different dimensions of a theory can be assessed. (2) criteria for the goodness of a theory. (3 )trade-offs between agreement with the natural world and representational consistency in the theory/model world.

Chat is not available.