This is the first comprehensive teaching resource and textbook for the teaching of MATLAB in the Neurosciences and in Psychology. MATLAB is unique in that it can be used to learn the entire empirical and experimental process, including stimulus generation, experimental control, data collection, data analysis and modeling. Thus a wide variety of computational problems can be addressed in a single programming environment. The idea is to empower advanced undergraduates and beginning graduate students by allowing them to design and implement their own analytical tools. As students advance in their research careers, they will have achieved the fluency required to understand and adapt more specialized tools as opposed to treating them as "black boxes". Virtually all computational approaches in the book are covered by using genuine experimental data that are either collected as part of the lab project or were collected in the labs of the authors, providing the casual student with the look and feel of real data. In some cases, published data from classical papers are used to illustrate important concepts, giving students a computational understanding of critically important research. The first comprehensive textbook on MATLAB with a focus for its application in neuroscience Problem based educational approach with many examples from neuroscience and cognitive psychology using real data Authors are award-winning educators with strong teaching experience
This example is illustrated in Figure 27.1C and D. ... We focus on the Neyman–Pearson and minimum error criteria. A Neyman–Pearson ideal observer is one that maximizes the probability of detection PD for a fixed value, say α, ...
In this book, Mike Cohen teaches brain scientists how to program in MATLAB, with a focus on applications most commonly used in neuroscience and psychology.
The focus of this text is on what can be considered the ‘golden trio’ in the signal processing field: averaging, Fourier analysis, and filtering.
This introductory text teaches students to understand, simulate, and analyze the complex behaviors of individual neurons and brain circuits.
This book addresses the snake in the room by providing a beginner’s introduction to the principles of computation and data analysis in neuroscience, using both Python and MATLAB, giving readers the ability to transcend platform tribalism ...
Cov(X,Y) σXσY Cor(X,Y) = where σX and σY are the standard deviations of X and Y. This is also often called the Pearson correlation, after Karl Pearson who studied extensively this and other measures of association.1 The correlation is ...
This book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them.
This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals.
Written specifically for those with no prior programming experience and minimal quantitative training, this accessible text walks behavioral science students and researchers through the process of programming using MATLAB.
2.14 (A) MATLAB Figure Window produced with program wilsoneuler.m with different integration time steps Δt. (b) Results of the program wilson.m that solves the same model with a higher-order ODE solver. two results in the spike train ...