Course Overview

Course Overview

The course is divided into four sections, or modules, describing the different stages of visual intelligence:

  • Module 1: Visual Stream. It explores experimental and theoretical aspects of hierarchical models of the ventral stream -- from HMAX to recent deep learning models.
  • Module 2: Memory and Executive Function. It explores a set of routines to integrate vision and cognition. This includes routines critical for understanding a scene, such as planning the next saccade and incorporating the visual information into working memory, as well as planning navigation and grasping.
  • Module 3: The Cognitive Core. This module explores the algorithms and circuit hardware involved in acquiring world knowledge that go beyond what is in the image and using it for visual understanding.
  • Module 4: Symbolic Compositional Models. It explores higher-level symbolic processes that are important for human visual understanding, including inferences on images and videos.

Each module will be introduced and discussed through 2 or 3 lectures that depict current theoretical aspects and experimental evidence. Each speaker will start and conclude the talk by situating their module in the context of the other ones. 

  • outline the present research plan for the module for the next 5 years, stressing what is already cast in stone and what is still open
  • provide the necessary background for the students
  • discuss -- and stimulate participants to think about -- possible interactions between modules.
  • challenge students to contribute ideas and to improve our plans

The class is an interesting opportunity for developing further our preliminary plans of the CBMM research proposal. For this reason, we encourage CBMM members to attend -- and contribute to -- the course.


Open to all graduate students. Undergraduates may enroll with permission of the instructors — interested students should contact Guy Ben-Yosef ( or Xavier Boix (

Class Meetings

Fridays 11:00 — 2:00
All classes will be in 46-3189, except the lecture on 10/20 that will be in 46-3002
First class meets on Friday, September 8


Students are required to complete a final project, which can take on different forms. A final paper on the project (5 pages, including text and figures, excluding references) is due by Friday, December 8. Each project will be completed by a group of 2 or 3 students. 

The project should relate computational and empirical findings on a topic that was presented in the course (see the schedule page for the list of topics to be covered). It can include an implementation component involving simulation and analysis of a model, or an empirical component involving the design of one or more pshychophyiscs experiments with some preliminary results. The project can also be related to your own research, if this is connected to the focus of the course. Another option for the project is to read a number of papers related to the computational and empirical aspects of a selected topic, and to provide a critique and suggestions for further studies. 


10% attendance + participation in class

90% project