CMOS Interface: Living Systems

Related lectures (32)

Page 3 of 4

Discusses the sources of neural variability and the reliability of spike timing.

Explores the firing threshold in the Hodgkin-Huxley model and the behavior of neurons under different current inputs.

Covers combining electrical, morphological, and molecular profiles to study single neurons.

Explores the profiling and behavior of ion channels, including their diversity and classes.

Explores data strategies for building neural circuits in simulation neuroscience.

Explores neocortical neuron classification, ion channel kinetics, challenges in modeling individual cells, and data integration.

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

Explores principles of data-driven modeling for simulating hippocampus microcircuits.

Explores weight sharing, filters, channels, and data augmentation in convolutional neural networks.

Explores convolutional neural networks, covering convolution, cross-correlation, max pooling, layer structure, and examples like LeNet5 and AlexNet.