Lectures related to Whole-cell recordings

Single Neuron Data Collection Techniques

Covers the methods for studying single neurons, including morphology and electrophysiology profiling.

Data strategies: building neural circuits

Explores data strategies for building neural circuits in simulation neuroscience.

Experimental Data Techniques: Caveats and Summary

Explores the study of single neurons, challenges in classification, and obtaining high-resolution data.

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.

Neurosciences I: Molecular Neuroscience and Neurodegeneration

Covers molecular neuroscience, neurodegeneration, cell types, neuron structure, and history of neuroscience breakthroughs.

Introduction to Systems Neuroscience: Memory Systems Overview

Introduces systems neuroscience, focusing on neural circuits, memory systems, and course logistics.

Modeling Electrophysiology: Different Scales

Covers modeling electrophysiology at different scales, discussing ion channels, single neurons, and microcircuits.

Observing the Brain: Neuroimaging Basics

Explores neuroimaging basics, brain network scales, connectivity, history, and physics, emphasizing the importance of understanding data at different scales.

The Microcircuits of Striatum in Silico

Explores the reconstruction of a full-scale mouse striatal cellular level model to integrate and interpret striatal data.

Data-Driven Modeling in Neuroscience: Meenakshi Khosla

By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.

Neuron Classification: Types and Challenges

Explores neuron classification, highlighting the importance of understanding brain complexity and the challenges in defining cell types.

Fundamentals of Brain Connectomics

Introduces the basics of brain connectomics, including terminology, data preprocessing, functional MRI, connectivity measures, and modular structure.

Computational Neuroscience: Biophysics & Modeling

Covers the fundamentals of computational neuroscience, focusing on biophysics and modeling.

Approaches and Rationale of Simulation Neuroscience

Explores the overview, rationale, and strategies of simulation neuroscience, emphasizing the challenges of reconstructing and simulating the brain.

Neuron Types: Classification and Morphological Diversity

Delves into neuron types, classification, challenges in reconstruction, staining techniques, and artifact correction, highlighting the importance of understanding brain complexity.

Modeling the electrical activity of the neuron

Explores the modeling of neuron electrical activity, including ion channels and concentrations, Nernst equation, and resting potential.

Spinal Cord Injuries: Neural Recording Systems

Explores the consequences of spinal cord injuries and the development of wireless neural recording systems.

Concluding remarks

Summarizes the course on brain function, highlighting progress and future directions.

Dendrite as a Cable

Discusses dendrites as cables, covering the cable equation derivation and current conservation in coupled compartments.

Injecting a current

Explains injecting current into a neuron, creating recordings, running simulations, and handling synapses.