Tel Aviv University
Analogies and Models in Science (Fall 2026)
Course Description: Analogical thinking is everywhere in science. It guides discoveries, helps build new models, and sometimes even serves to justify hypotheses. Yet its status is contested. Some hold that a general theory of analogical inference can be formulated, while others argue that the strength of an analogy depends on the details of the case at hand. In this seminar we will examine when and why analogies succeed or fail as a tool of scientific inference. In the first part of the seminar we will consider how we think by means of analogies, the difference between analogy and metaphor, and the role of analogy as a heuristic tool in science. In the second part we will ask what a scientific model is in general, and what an analogical model is in particular. We will examine in what sense a model represents another system, what the relation is between similarity and representation, and what makes an analogy successful. In the last part of the seminar we will examine how analogies function, as they are manifested in several case studies of analogical models from the history of science.
Guided Reading: Reading Classic Texts (Fall 2026)
Course Description: Reading foundational texts from the history of science and the philosophy of science. This year we are reading Hasok Chang's Inventing Temperature: Measurement and Scientific Progress (2004).Â
Causation and Explanation in Neuroscience (Spring 2027)
Course Description: Scientific explanations in neuroscience often rely on causal models. In a complex system such as the brain, identifying causal relations, and the way they contribute to explanation, raises special difficulties. In this seminar we will examine how scientists explain phenomena and processes in the brain, and the place of causation in these explanations. We will discuss different approaches to scientific explanation and to causation, and how they are expressed in neuroscience. We will examine the idea of causal intervention, how competing causal explanations are adjudicated, and central methods of causal inference. Finally, we will discuss the limitations of causal explanations in neuroscience, among them the difficulty of determining which variables are relevant in complex systems, of representing causal relations that unfold over time, and of specifying the background conditions on which causal claims depend.
Philosophy of Science II (Spring 2027)
Course Description: The course aims to become closely acquainted with central issues in contemporary philosophy of science, through a close study of three philosophical aspects of scientific activity: (a) the confirmation of scientific hypotheses on the basis of empirical evidence; (b) the clarification and analysis of the concept of explanation as it is used in science; (c) the way scientific models represent empirical phenomena, and what can be learned from them about reality.