Storage Capacity: Prototypes and Neuronal Dynamics

Related lectures (32)

Page 3 of 4

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Covers the propagation of uncertainty in model measurements and the importance of understanding errors.

Explores the tradeoff between risk and return in portfolios, the benefits of diversification, and the impact of correlation on portfolio risk.

Covers risk and return tradeoffs in portfolios, diversification benefits, and the efficient frontier with multiple assets.

Explores the Schrödinger equation in quantum mechanics, numerical methods, and properties of observables.

Covers conditional density, independence of random variables, expectation, and variance calculation.

Explores attractor networks, spiking neurons, memory data, and realistic networks in neural dynamics.

Explores memory encoding, neuronal plasticity, types of memory, brain regions, and clinical cases.

Introduces the t-test for assessing categorical effects on quantitative outcomes, covering hypothesis testing, assumptions, and alternative tests.

Covers the characteristics and importance of the normal distribution, including examples and treatment scenarios.