Neuroscience
A comprehensive graduate-level course on neuroscience—from neural coding and synaptic transmission through systems neuroscience, computational models, brain imaging, and brain-computer interfaces.
Course Overview
Neuroscience spans the study of individual neurons to the emergent properties of neural circuits and whole-brain systems. This course integrates cellular, systems, and computational perspectives to provide a unified understanding of how the brain processes information, generates behavior, and gives rise to cognition.
What You'll Learn
- • Neural coding and information processing
- • Synaptic transmission and plasticity
- • Neural circuits and sensory processing
- • Motor systems, learning, and memory
- • Decision making and consciousness
- • Computational models of neural systems
- • Brain imaging and connectomics
- • Brain-computer interfaces and neural engineering
Prerequisites
• Probability and statistics
• Programming basics (helpful)
References
- • E. R. Kandel et al., Principles of Neural Science (6th ed.)
- • P. Dayan & L. F. Abbott, Theoretical Neuroscience
- • W. Gerstner et al., Neuronal Dynamics
- • M. F. Bear, B. W. Connors & M. A. Paradiso, Neuroscience: Exploring the Brain
Ninja Nerd Neurology Library
Undergraduate-level companion videos from the Ninja Nerd Neurology series — comprehensive clinical neuroanatomy, tracts, autonomic nervous system, and cranial-nerve coverage. Use as a refresher before the computational and systems chapters, or as a clinical-anatomy reference when you encounter unfamiliar structures in the quantitative parts.
Brain & Spine Anatomy Models
Anatomy of the Brain | Model
Anatomy of the Brain | Dissectible Model
Ventricles of the Brain | Anatomy Model
Anatomy of the Spine | Model
Cellular Neurology
Neuron Anatomy & Function
Resting Membrane, Graded & Action Potentials
Glial Cells: Astrocytes, Oligodendrocytes, Schwann, Ependymal, Microglia
Cerebrum & Cortex
Cerebral Cortex Anatomy & Function: Overview
Frontal Lobe Anatomy & Function
Parietal Lobe Anatomy & Function
Temporal Lobe Anatomy & Function
Occipital Lobe Anatomy & Function
Subcortical Structures & Brainstem
Basal Ganglia: Direct & Indirect Pathways
Hypothalamus Anatomy & Function
Thalamus Anatomy & Function
Limbic System Anatomy & Function
Midbrain Anatomy & Function
Pons Anatomy & Function
Medulla Anatomy & Function
Cerebellum Anatomy & Function
Brain Meninges & Hematomas (Epidural, Subdural, Subarachnoid, Intracerebral)
Spinal Cord Structure
Gross Anatomy of the Spinal Cord & Spinal Nerves
Spinal Cord: Gray Matter Structure & Function
Spinal Cord: White Matter Structure & Function
Spinal Cord Meninges
Spinal Cord Blood Supply
Ascending Tracts & Pain
Dorsal Column: Medial Lemniscus Pathway
Spinothalamic Tract
Spinocerebellar Tract
Pain Modulation: Gate Control Theory
Descending Tracts
Descending Tracts: Overview
Corticobulbar Tract
Corticospinal Tract
Vestibulospinal Tract
Pontine Reticulospinal Tract
Rubrospinal Tract
Medullary Reticulospinal Tract
Reflexes & Motor-Neuron Lesions
Stretch Reflex | Muscle Spindle
Golgi Tendon Organ Reflex (GTO)
Upper vs Lower Motor Neuron Lesion (UMN vs LMN)
Autonomic Nervous System
Autonomic Nervous System: Overview
Sympathetic Nervous System
Adrenergic Receptors
Parasympathetic Nervous System
Cholinergic Receptors
Enteric Nervous System
Cranial Nerves I–XII
Cranial Nerves: Overview
CN I: Olfactory Nerve
CN II: Optic Nerve — Visual Pathway & Lesions
CN III: Oculomotor Nerve
CN IV: Trochlear Nerve
CN V: Trigeminal Nerve
CN VI: Abducens Nerve
CN VII: Facial Nerve
CN VIII: Vestibulocochlear — Auditory Pathway
CN VIII: Vestibulocochlear — Vestibular Pathway
CN IX: Glossopharyngeal Nerve
CN X: Vagus Nerve
CN XI: Accessory Nerve
CN XII: Hypoglossal Nerve
Gustation (Taste Pathway)
Plexuses & Peripheral Nerves
Cervical Plexus
Brachial Plexus
Lumbar Plexus
Sacral Plexus
Nerve Injury & Repair: Wallerian Degeneration & Regeneration
Neuroscience for Machine Learners
A week-by-week graduate course (33 lectures) covering neuron biophysics, synaptic dynamics, network models, the connectome, learning rules (STDP, surrogate gradients), neural-data analysis, decision making, and neuromorphic computing — a natural companion to the systems-and-computational chapters of this course.
Find out more at neuro4ml.github.io.
Week 0 — Why Neuroscience? & Course Outline
W0 V0 — Why Neuroscience?
W0 V1 — Course Outline
W0 V2 — History of Neuroscience & Machine Learning
W0 V3 — Challenges for ML & Neuroscience
Week 1 — The Neuron
W1 V0 — Neuron Structure
W1 V1 — Neuron Function
W1 V2 — Abstract Models
W1 V3 — Biophysical Models
W1 V4 — Exercises
Week 2 — Synapses & Networks
W2 V0 — Synapses 1
W2 V1 — Synapses 2
W2 V2 — Networks
W2 V3 — Synapse Models
W2 V4 — Network Models
W2 V5 — Exercises
Week 3 — The Connectome
W3 V0 — Connectome
W3 V1 — Humans
W3 V2 — Exercise
Week 4 — Learning Rules
W4 V0 — Types of Learning
W4 V1 — Rate-based Models
W4 V2 — STDP (Spike-Timing-Dependent Plasticity)
Week 5 — Gradients in Spiking Networks
W5 V0 — Spiking Is Not Differentiable
W5 V1 — Limited Gradients
W5 V2 — Surrogate Gradients
Week 6 — Observing, Analysing, Manipulating
W6 V0 — Observing
W6 V1 — Analysing
W6 V2 — Manipulating
W6 V4 — Exercise
Week 7 — Decision Making
W7 V0 — Decision Making
Week 8 — Neuromorphic Computing
W8 V0 — Intro to Neuromorphic Devices
W8 V1 — Neuromorphic Computing
W8 V2 — Neuromorphic Sensing & Applications
Week 9 — Reflections
W9 V0 — Does Neuroscience Work?
W9 V1 — What Are Spikes For?
Course Structure
Part I: Neural Basics
Neural coding, synaptic transmission, neural circuits, and sensory processing.
Part II: Systems Neuroscience
Motor systems, learning and memory, decision making, and attention and consciousness.
Part III: Computational
Computational models, neural networks, brain imaging, and connectomics.
Part IV: Applied Neuroscience
Neurological disorders, neuropharmacology, brain-computer interfaces, and neural engineering.
Key Equations
Hodgkin-Huxley Equation
Describes action potential generation in neurons
Cable Equation
Passive signal propagation along dendrites and axons
Spike Train Information
Mutual information between stimulus and neural response
STDP Learning Rule
Spike-timing-dependent plasticity: synaptic weight change
Drift-Diffusion Model
Accumulation of evidence for perceptual decision making
BOLD Signal Model
Hemodynamic response convolution in fMRI