The Neurocomputation Laboratory

The research in the laboratory is done under the supervision of Prof. Larry M. Manevitz, Department of Computer Science, University of Haifa.



The field of neurocomputation is concerned with the possibility of computation in computers by following the paradigm and analysis of computation that occurs in neurons and the brain. In recent years this has resulted in breakthroughs in pattern recognition, machine learning theory, clustering, associative memory and fault tolerant computation.

Consequently, the precision resulting from the computational and mathematical viewpoint has led to insights helping to clarify aspects of one of the ultimate human research endeavors: understanding the manner in which human thought emerges from the organization of the human brain.

In our laboratory, we focus on three main objectives:

  1. Isolating new techniques concerned with computation and storage of spatio-temporal patterns
  2. Modeling psychological theories of human cognitive behavior
  3. Applying and developing novel techniques, especially feature selection and machine learning tools towards automated pattern recognition of brain behavior

See “Current and Recent Projects” tab for specifics including one and two-class methodologies for identifying cognitive tasks from fMRI scans, development of advanced topologically constrained liquid state machines and their applications (e.g. for model free prediction of BOLD signal), and the use of machine learning tools to show the existence and some properties of two distinct human declarative memory systems (with and without, e.g. the hippocampus)

Course Links

Introduction to Basic Principles of Machine Learning (2016) for Data Science Program of the Faculty of Management