Looking for neurobiology books? We have gathered a collection of free neurobiology books in PDF covering neuroanatomy, cellular and molecular neurobiology, cognitive neuroscience, and computational neuroscience.
These textbooks explain how the brain and nervous system work, from the structure of neurons to the neural basis of thought and behavior. Whether you study biology, medicine, or just want to understand the science behind the brain, you will find something here.
Browse our collection below or pick a section by topic. Every book is free to read online or download as PDF.
General Neurobiology Books
Neurobiology is the branch of biology that studies the structure and function of the nervous system. These books provide a broad introduction, from basic principles to how neural circuits produce behavior.
A comprehensive open textbook covering neuron structure, neuronal communication, sensory and motor systems, and behavioral neuroscience. Designed for undergraduate courses with clear explanations and original illustrations.
A professionally designed primer by the Society for Neuroscience covering brain development, senses, movement, learning, memory, aging, and neurological disorders. Ideal for readers new to brain science.
An introductory booklet by the British Neuroscience Association and SfN covering neurons, drugs, brain development, vision, memory, stress, and neurological diseases in accessible language.
Neuroanatomy focuses on the physical structure of the brain and nervous system. These books cover brain regions, neural pathways, and the organization of the central and peripheral nervous systems.
A board review guide covering gross anatomy of the brain, spinal cord tracts, cranial nerves, and clinical neuroanatomy. Includes over 575 USMLE-style questions for self-assessment.
A concise illustrated guide to neuroanatomy for medical students covering brain regions, spinal cord, cranial nerves, and autonomic nervous system. Written by a professor emeritus at the University of Western Ontario.
At the cellular level, neurobiology studies how neurons communicate through electrical and chemical signals. These books cover action potentials, synaptic transmission, and the molecular mechanisms that drive neural function.
A comprehensive reference covering molecular and cellular foundations of neural function including neurotransmitters, signal transduction, myelin, and neurological disease mechanisms. A standard text in the field for over four decades.
George J. Siegel, R. Wayne Albers, Scott T. Brady, Donald L. Price
Lecture notes from Carnegie Mellon University covering synaptic transmission, neurotransmitter release, postsynaptic potentials, and neural integration. Includes clear diagrams of synaptic mechanisms.
A focused guide on synaptic transmission covering neurotransmitter synthesis, vesicle release, receptor interaction, and signal termination. Explains both ionotropic and metabotropic receptor mechanisms.
Cognitive neuroscience explores the neural basis of perception, memory, attention, and decision-making. These books bridge the gap between brain biology and mental processes.
A multi-author handbook covering development, evolution, perception, attention, memory, language, emotion, and consciousness from a neuroscience perspective. Edited by the founder of the field of cognitive neuroscience.
A leading textbook integrating neuroscience methods with cognitive psychology. Covers brain imaging, hemispheric specialization, attention, memory, language, and executive functions with rich illustrations.
Michael S. Gazzaniga, Richard B. Ivry, George R. Mangun
Computational neuroscience uses mathematical models to understand how neural systems process information. These books cover spiking neuron models, network dynamics, and brain simulations.
A focused treatment of biologically realistic neuron models covering integrate-and-fire models, Hodgkin-Huxley equations, population dynamics, and synaptic plasticity. Combines mathematical rigor with neuroscience applications.
A review of third-generation spiking neural networks covering computational power, neuron models, network architectures, and learning rules. Provides a bridge between biological neural computation and machine learning.
