Library

Overview of books for our library

Neuroscience

• Principles of Neural Science, by Eric R. Kandel (Editor), James H. Schwartz (Editor), Thomas M. Jessell (Editor), Steven A. Siegelbaum (Editor), A. J. Hudspeth (Editor)

• Neuroscience by Dale Purves and George J. Augustine

• Neuroscience: Exploring the Brain by Mark F. Bear and Barry W. Connors

Connectome

• Handbook of Brain Connectivity (Understanding Complex Systems) by Viktor K. Jirsa (Editor), A.R. McIntosh (Editor)

• Coordinated Activity in the Brain: Measurements and Relevance to Brain Function and Behavior (Springer Series in Computational Neuroscience) by Jose Luis Perez Velazquez (Editor), Richard Wennberg (Editor)

Computational Neuroscience

• Principles of Computational Modelling in Neuroscience, by David Sterratt (Author), Bruce Graham (Author), Andrew Gillies (Author)

• Biophysics of Computation: Information Processing in Single Neurons by Christof Koch (Author)

• Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems by Laurence F. Abbott (Author), Peter Dayan (Author)

• Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition by Wulfram Gerstner (Author), Werner M. Kistler (Author), Richard Naud (Author), Liam Paninski (Author)

• Spikes: Exploring the Neural Code (Computational Neuroscience) by Fred Rieke and David Warland

• The Handbook of Brain Theory and Neural Networks (A Bradford Book) by Michael A. Arbib

• Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Computational Neuroscience Series) by Eugene M. Izhikevich (Author), Terrence J. Sejnowski

• Handbook of Neural Activity Measurement by Romain Brette, Alain Destexhe

• Introduction to Theoretical Neurobiology Vol 1: Linear Cable Theory and Dendritic Structure

• Introduction to Theoretical Neurobiology Vol 2: Nonlinear and Stochastic Theories

• Modeling in the Neurosciences: From Biological Systems to Neuromimetic Robotics​

• Computational Neuroscience: A Comprehensive Approach

• Mathematics for Neuroscientist

• Mathematical Foundations of Neuroscience

• Waves in Neural Media: From single Neurons to Fields

• Neural Fields: Theory and Applications

Computational Biology

• Random Walks in Biology by Howard C. Berg

• Biophysics: Searching for Principles by William Bialek

• Bridging Time Scales: Molecular Simulations for the Next Decade

• Stochastic Processes in Cell Biology

• Mathematical Biology: I. An Introduction (Interdisciplinary Applied Mathematics) (Pt. 1) by J.D. Murray

• Mathematical Biology II: Spatial Models and Biomedical Applications (Interdisciplinary Applied Mathematics) (v. 2) by J.D. Murray

Math

• Fourier Analysis: An Introduction (Princeton Lectures in Analysis, Volume 1) by Elias M. Stein and Rami Shakarchi

• Complex Analysis (Princeton Lectures in Analysis, No. 2) by Elias M. Stein and Rami Shakarchi

• Real Analysis: Measure Theory, Integration, and Hilbert Spaces (Princeton Lectures in Analysis) (Bk. 3) by Elias M. Stein and Rami Shakarchi

• Functional Analysis: Introduction to Further Topics in Analysis (Princeton Lectures in Analysis) (Bk. 4) by Elias M. Stein and Rami Shakarchi

• Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, Second Edition (Studies in Nonlinearity) (Volume 1) by Steven H. Strogatz

• Linear Algebra and Its Applications by Gilbert Strang

• Introduction to Applied Mathematics, by Gilbert Strang

• Differential Equations and Linear Algebra, by Gilbert Strang

Stats

• Statistics: A Guide to the Use of Statistical Methods in the Physical Sciences by R. J. Barlow

• All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics) by Larry Wasserman

• All of Nonparametric Statistics (Springer Texts in Statistics) by Larry Wasserman

Bayesian

• Bayesian Data Analysis by Andrew Gelman (Author), John B. Carlin (Author), Hal S. Stern (Author), David B. Dunson (Author), Aki Vehtari (Author), Donald B. Rubin (Author)

• Statistical Rethinking: A Bayesian Course with Examples in R and Stan by Richard McElreath

Causal inference

• Causality: Models, Reasoning and Inference by Judea Pearl

• Causal Inference in Statistics: A Primer by Judea Pearl and Madelyn Glymour

• Mostly Harmless Econometrics: An Empiricist's Companion by Joshua D. Angrist and Jörn-Steffen Pischke

Analysis

• Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators (Wiley Series in Probability and Statistics) by Tailen Hsing and Randall Eubank

• Analysis of Neural Data by Kass, Robert E., Eden, Uri, Brown, Emery

Machine Learning

• Deep Learning with Python by Francois Chollet

• Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent by Aurélien Géron

• Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto

• The Elements of Statistical Learning: Data Mining, Inference, and Prediction, (Springer Series in Statistics) by Trevor Hastie (Author), Robert Tibshirani (Author), Jerome Friedman (Author)

• Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig

Complexity and Information Theory

• Information Theory: A Tutorial Introduction Paperback by James V Stone (Author)

• Information Theory, Inference and Learning Algorithms by David J.C. MacKay

• Information, Physics, and Computation (Oxford Graduate Texts) by Marc Mézard and Andrea Montanari

• The Nonlinear World: Conceptual Analysis and Phenomenology (Springer Series in Synergetics) by Yoshitsugu Oono

• Six Degrees: The Science of a Connected Age Reprint Edition by Duncan J. Watts (Author)

• Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life by Albert-Laszlo Barabasi (Author)

• Complexity: A Guided Tour by Melanie Mitchell (Author)

• Supercooperators: The Mathematics of Evolution, Altruism and Human Behaviour, (Or, Why We Need Each Other to Succeed) by M A Nowak (Author)

• Graph Theory and Complex Networks: An Introduction by Maarten van Steen (Author)

• Networks: An Introduction by Mark Newman (Author)

• Dynamical Processes on Complex Networks by Alain Barrat (Author), Marc Barthélemy (Author), Alessandro Vespignani (Author)

• Evolution of Networks: From Biological Nets to the Internet and WWW (Physics) by S. N. Dorogovtsev (Author), J.F.F. Mendes (Author)

• Graph Spectra for Complex Networks by Piet Van Mieghem

• The Structure of Complex Networks: Theory and Applications by Ernesto Estrada (Author)

• Networks of the Brain (MIT Press) by Olaf Sporns (Author)

Signal Processing

• Digital Signal Processing by Alan V. Oppenheim and Ronald W. Schafer

• Independent Component Analysis by Aapo Hyvarinen, Erkki Oja, and Juha Karhunen

Biology

• Life: The Science of Biology, by David E. Sadava (Author), David M. Hillis (Author), H. Craig Heller (Author), May Berenbaum (Author)

General

• The Structure of Scientific Revolutions by Thomas S. Kuhn (Author)

• Sync by Strogatz

Wanted

• Good book on probability theory

• Brain atlases