Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
This book takes a multiscale overview and theoretical framework for all existing brain imaging modalities. It also presents technological development for data fusion and underlying biophysical models. The book also provides problems and exercises useful for undergraduate and graduate courses.
Biophysics of Brain Imaging is broken up into 3 parts. Part 1: Modeling Observations and Microscopic Phenomena provides the physical and physiological foundation of all brain imaging modalities. Part 2 (Edited): Measuring and Modeling Emergent Mesoscopic Phenomena examines recording techniques and biophysical models used today to represent the mesoscale of the brain, the voxel. Part 3: Hypothesis Testing and Applications discusses methods to analyze brain imaging data and their applications to evaluate signatures in a variety of diseases, e.g., epilepsy, AD, and migraine.
This book is intended for undergraduate and graduate level students in Computational Neuroscience, Medical Imaging, Electrophysiology, and Brain Data Analysis and Modeling courses.
Figure slides are available to adopting professors.
Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Memmo's summaries are gold before exams. I don't have to re-read 800 pages two weeks before — just the important parts.
The AI chat has saved me the night before an exam more than once. I just keep asking until I get it — no waiting on a study group to reply.
The quizzes hit exactly what I need to know. Memmo tracks what I get stuck on — so I only practice what's worth it.
Flashcards with spaced repetition are magic. Memmo knows when I'm about to forget something and brings it back.
The AI podcasts are my favorite. I listen on my way to school and get a recap without sitting at a computer.
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