version 2023-03-19


Image of brain and neuron HPS 2359 Methods, Models, and Measurements in the Neural, Behavior, and Cognitive Sciences

Spring 2023 Schedule and Syllabus
Meeting time; location: T 2-4:30; CL 1008C


(Prof.) Colin Allen <>
Office: CL 1109H
Office hours: M 3:20-5:00 in CL 1109H (and on Zoom by appointment)

Course Description

Mathematical, and statistical treatments of behavior and cognition were central to the emergence of psychology as scientific discipline in the late 19th C., were a driving force for developments in statistical testing, in measurement theory, and in computational modeling during the 20th C., and continue to be important for ongoing debates about the so-called replication crisis in psychology, and different views about the value of formal, mathematical, and computational models in cognitive science. Other topics of interest to philosophy of science include the interplay between statistical models and experimental design, particularly where the latter rely on methods that generate large amounts of noisy data, such as EEG or fMRI. Bayesian, information theoretic, dynamical, and mechanistic approaches to explanation all have different implications for understanding the relationship between cognition and nervous systems.

The spring 2023 version of this course will focus largely on the subdiscipline known as mathematical psychology, covering questions about the nature and significance of distinctions among process and phenomenal models, as well as the relative merits of different modeling frameworks. These topics will lead us to more general issues concerning the epistemic and explanatory status of cognitive models, pragmatism in modeling choices, and methods for evaluating models as well as the relationship of cognitive models to neuroscience.

There will be maths! (But we will work through it together.) (And see Additional Resources below the schedule.)

Course Objectives

Aside from acquiring the necessary background in cognitive modeling, the main goal of this seminar is for you to develop a research paper on any philosophical issue raised during the course. You will write a proposal, draft, engage peer reviews, and the final paper. You will also be asked to give at least one presentation based on the reading list, and you will also give a presentation based on your developing research ideas during the last month of the course.


  1. Readings provided electronically through Canvas. They are organized into a folder and subfolder. In the upper level folder at are papers that ideally I'd like to get to. In the "Pool" subfolder are other things that may be added or subsituted for the list.

Schedule of Readings and Presentations

This is a rough guide only. We are going to adjust this as we go along, based on participant interest.


DateTopicReading Assignments
Tue 01/17 Promise and difficulties of mathematical modelsNavarro 2021
Luce 1995
Tue 01/24 Difficulties Luce 1995
Estes 2002
Tue 01/31 Dynamics / Concepts & categories Beer 2023
Tue 02/07 Concepts & categories cont'd Nosofsky & Zaki 2002
Kruschke 2008
Tue 02/14 Model Selection Shiffrin 2008
Evans 2019
Tue 02/21 Predicting mathpsych Luce 1999
Townsend 2008
Tue 02/28 Constructing models van Rooij & Baggio 2021
Boorsboom et al. 2021
Tue 03/07 Spring Break, no class!
Tue 03/14 Theory construction van Rooij 2020 (Choi)
Vigo 2021
Tue 03/21 Bayesian Mathpsych? Griffiths et al. 2010 (Cole)
Beck et al. 2008
Tue 03/28 Neuro Mathpsych? Palmieri et al. 2017 (Jenny)
Soto and Ashby 2023
Tue 04/04 Animals Smith et al. 2014 (Madeleine)
Allen 2014
Tue 04/11 Cognitive & Associative Buckner 2011 (Sameera)
• maybe???--Raijmakers & Shiffrin 1981
Tue 04/18 Philosophy of models Wimsatt 1987
Cummins 2000 (Joshua)
Batterman & Rice 2014

Additional Resources

If you want some exceptionally clear, wonderfully animated, and often humorous introductions/refreshers for some of the mathematics we'll be faced with, I highly recommend the videos put out by Grant Sanderson, aka 3blue1brown. The following are particularly relevant as we get further into the course: And although it's got nothing to do with the course, this one is a wonderful illustration of the style: This problem seems hard...

Statement for Students with Disabilities
The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please visit Pitt Student Affairs Disability Resources and Services for further information.

Statement about Academic Misconduct

Students in this course will be expected to comply with the University of Pittsburgh’s Policy on Academic Integrity.