Representational Similarity Analysis

Representational Similarity Analysis: Understanding Representations in Minds and Machines is the first book on representational similarity analysis that surveys advances in computational neuroscience. First off, the book introduces the reader to representation patterns and relation to neuroscience and psychology. The second section explores how to understand the data, including data modalities in both modern neuroscience and AI research. The third section reviews Representational similarity analysis (RSA) in depth, covering all aspects from metrics, interpretation, and modeling. Next, the book offers tutorials of RSA computations, including setup, case studies, and practical considerations. The last section summarizes the possible future frontiers of representational studies.

• Provides a timely and comprehensive review of representational similarity analysis
• Proposes a new, unified formulation of statistical inference methods for comparing brain and model representations
• Covers a vast array of special topics and applications, including both vision and language to help illustrate the wide use in understanding neural information processing
• Presents convincing case studies and hands-on tutorials for a broad audience of scientists, including neuroscience, psychology, and computer science