# Neuromodeling (M1 ENS Ulm)

Teacher: Manuel Beiran

## Introductive tutorial: Evolution of a population

Introductive tutorial

## Problem Set 2: Quantitative models of behavior

Problem Set 2: Quantitative models of behavior.

## [Problem Set 2 Quantitative models of behavior] Problem 1: Rescola-Wagner Rule

Problem 1: The Rescola-Wagner Rule

## [Problem Set 2 Quantitative models of behavior] Problem 2: Decision strategy for flower sampling by bees

Problem 2: Decision strategy for flower sampling by bees.

## [Problem Set 2 Quantitative models of behavior] Problem 3: The drift diffusion model of decision-making

Problem 3: The drift diffusion model of decision-making.

## [Problem Set 2 Quantitative models of behavior] Problem 4: Reinforcement learning in a maze

Problem 4: Reinforcement learning in a maze.

## Problem Set 3: Spike trains

Problem 1: Poisson spike trains.

## [Problem Set 3 Spike trains] Problem 1: Poisson spike trains

Problem 1: Poisson spike trains.

## [Problem Set 3 Spike trains] Problem 2: Analysis of spike trains

Problem 2: Analysis of spike train.

## [Problem Set 3 Spike trains] Problem 3: Integrate-and-Fire neuron

Problem 3: Integrate-and-Fire neuron.

## [Problem Set 3 Spike trains] Problem 4: The Hodgkin-Huxley model

Problem 4: the Hodgkin-Huxley model.

## Problem Set 4: Networks

Problem Set 4: Networks.

## [Problem Set 4 Networks] Problem 1: Neuron with Autapse

Problem 1: Neuron with Autapse.

## [Problem Set 4 Networks] Problem 2: Circuit with mutual inhibition

Problem 2: Circuit with mutual inhibition.

## [Problem Set 4 Networks] Problem 3: Hopfield model

Problem 3: Hopfield model.

## Lecture 1: Neuromodeling

Manuel Beiran: manuel.beiran-at-ens.fr

## Lecture 2: Rescorla-Wagner Rule

Classical conditioning

## Lecture 3: Exploration-exploitation dilemma

Computational model of behavior:

## Lecture 4: Drift-diffusion models

Reminder: differential equations we’ll encounter

## Lecture 5: Integrate-and-fire neurons

A Cell ⟺ An RC circuit

## Lecture 6: Hodgkin-Huxley model

Cell membrane = semi-permeable

## [Project] Coherent Patterns of Activity from Chaotic Neural Networks

Final Project: Coherent Patterns of Activity from Chaotic Neural Networks.