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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.

Demographic Transition: Explained and Analyzed

Explores the concept of demographic transition, analyzing the shift from high to low birth and death rates in populations.

Neural Networks: Hierarchical Models and Odor Taxis

Covers neural function, hierarchical models, odor taxis behaviors, and disparate circuit parameters in 18 slides.

Generalized Integrate-and-Fire Models

Explores the Generalized Integrate-and-Fire Model and the Nonlinear Integrate-and-Fire Model.

Variability of Spike Trains

Explores the variability of spike trains in computational neuroscience, covering experiments, sources of variability, and stochastic spike arrival and firing.

Artificial Limbs: Neither Body nor Tool

Delves into the challenges of achieving full embodiment with artificial limbs and the importance of maintaining a sense of collective unity.

Integrative Benchmarking: Advancing System Models of Human Intelligence

Explores advancing system models of human intelligence through integrative benchmarking and the importance of Brain-Score for fair model comparisons.

Dynamical modeling, decoding, and control of multiscale brain network activity

Explores dynamical modeling, decoding, and control of brain network activity for personalized therapy.

Modeling Neuronal Activity

Explores modeling neuronal activity, including firing rates, responses to stimuli, and network behavior.

Networks of Spiking Neurons

Explores networks of spiking neurons, mean-field models, transfer functions, and predictions of state space and neuron behavior.