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UE946 - MOD 202 - Computational neuroscience methods
Lieu et planning
-
Autre lieu Paris
ENS, 29 rue d'Ulm 75005 Paris
2nd semestre / hebdomadaire, vendredi 14:00-17:00
du 5 février 2021 au 21 mai 2021
Description
Dernière modification : 7 avril 2021 14:58
- Type d'UE
- Enseignements fondamentaux de master
- Disciplines
- Psychologie et sciences cognitives
- Page web
- https://cogmaster.ens.psl.eu/en/program/m1-program-13570
- Langues
- anglais
- Mots-clés
- Méthodes et techniques des sciences sociales Sciences cognitives
- Aires culturelles
- -
Intervenant·e·s
- Srdjan Ostojic [référent·e] directeur de recherche, CNRS
The aim of this practical course is to learn to implement computational models of neural systems, and to perform basic analyses of neural data. The students will use Python to work on several projects that include:
1. simulating a spiking neuron,
2. simulating a network of neurons,
3. estimating a receptive field from neural data,
4. estimating the information contained in neural responses,
5. simulating an animal’s behaviour during reinforcement learning.
Introduction to computational modelling in Python
Behavioral modelling: Rescorla-Wagner rule
Behavioral modelling: instrumental conditioning
Behavioral modelling: drift-diffusion model
Neural variability and spike-train statistics
Integrate-and-fire neurons
Firing-rate models
Hopfield networks
Master
-
Méthodologie
– Sciences cognitives
– M1/S2
Suivi et validation – semestriel hebdomadaire = 4 ECTS
MCC – contrôle continu
Renseignements
- Contacts additionnels
- cogmaster@psl.eu
- Informations pratiques
The complete syllabus of the course is available on the Cogmaster's website. For any information, please contact the secretariat of the Cogmaster.
Registration procedure (external students) : https://cogmaster.ens.psl.eu/en/students/external-students-13501
- Direction de travaux des étudiants
- -
- Réception des candidats
- -
- Pré-requis
Basics of programming with Python.
Dernière modification : 7 avril 2021 14:58
- Type d'UE
- Enseignements fondamentaux de master
- Disciplines
- Psychologie et sciences cognitives
- Page web
- https://cogmaster.ens.psl.eu/en/program/m1-program-13570
- Langues
- anglais
- Mots-clés
- Méthodes et techniques des sciences sociales Sciences cognitives
- Aires culturelles
- -
Intervenant·e·s
- Srdjan Ostojic [référent·e] directeur de recherche, CNRS
The aim of this practical course is to learn to implement computational models of neural systems, and to perform basic analyses of neural data. The students will use Python to work on several projects that include:
1. simulating a spiking neuron,
2. simulating a network of neurons,
3. estimating a receptive field from neural data,
4. estimating the information contained in neural responses,
5. simulating an animal’s behaviour during reinforcement learning.
Introduction to computational modelling in Python
Behavioral modelling: Rescorla-Wagner rule
Behavioral modelling: instrumental conditioning
Behavioral modelling: drift-diffusion model
Neural variability and spike-train statistics
Integrate-and-fire neurons
Firing-rate models
Hopfield networks
-
Méthodologie
– Sciences cognitives
– M1/S2
Suivi et validation – semestriel hebdomadaire = 4 ECTS
MCC – contrôle continu
- Contacts additionnels
- cogmaster@psl.eu
- Informations pratiques
The complete syllabus of the course is available on the Cogmaster's website. For any information, please contact the secretariat of the Cogmaster.
Registration procedure (external students) : https://cogmaster.ens.psl.eu/en/students/external-students-13501
- Direction de travaux des étudiants
- -
- Réception des candidats
- -
- Pré-requis
Basics of programming with Python.
-
Autre lieu Paris
ENS, 29 rue d'Ulm 75005 Paris
2nd semestre / hebdomadaire, vendredi 14:00-17:00
du 5 février 2021 au 21 mai 2021