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UE473 - Atelier Modélisation computationnelle (MOD 201)
Lieu et planning
-
ENS-Ulm
75005 Paris
2nd semestre / hebdomadaire, vendredi 14:00-16:00
du 10 septembre 2021 au 14 janvier 2022
Description
Dernière modification : 18 juin 2021 12:52
- Type d'UE
- Enseignements fondamentaux de master
- Disciplines
- Psychologie et sciences cognitives
- Page web
- https://docs.google.com/document/d/1eZxBa6RQDNsBb2KXVS3C6iedI9Lb-oNI36K4Z44ZYGQ/edit
- Langues
- anglais
- Mots-clés
- -
- 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:
- simulating a spiking neuron,
- simulating a network of neurons,
- estimating a receptive field from neural data,
- estimating the information contained in neural responses,
- simulating an animal’s behaviour during reinforcement learning.
Prerequisites:
Basics of Programming with Python.
The students will learn :
- to understand the basic mechanisms underlying classical computational models;
- to derive basic analytical predictions;
- to implement models numerically;
- to report work in a scientific way.
Master
-
Séminaires de tronc commun
– Sciences cognitives
– M1/S2
Suivi et validation – semestriel hebdomadaire = 4 ECTS
MCC – CC +Examen
Renseignements
- Contacts additionnels
- -
- Informations pratiques
- -
- Direction de travaux des étudiants
- -
- Réception des candidats
- -
- Pré-requis
- -
Dernière modification : 18 juin 2021 12:52
- Type d'UE
- Enseignements fondamentaux de master
- Disciplines
- Psychologie et sciences cognitives
- Page web
- https://docs.google.com/document/d/1eZxBa6RQDNsBb2KXVS3C6iedI9Lb-oNI36K4Z44ZYGQ/edit
- Langues
- anglais
- Mots-clés
- -
- 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:
- simulating a spiking neuron,
- simulating a network of neurons,
- estimating a receptive field from neural data,
- estimating the information contained in neural responses,
- simulating an animal’s behaviour during reinforcement learning.
Prerequisites:
Basics of Programming with Python.
The students will learn :
- to understand the basic mechanisms underlying classical computational models;
- to derive basic analytical predictions;
- to implement models numerically;
- to report work in a scientific way.
-
Séminaires de tronc commun
– Sciences cognitives
– M1/S2
Suivi et validation – semestriel hebdomadaire = 4 ECTS
MCC – CC +Examen
- Contacts additionnels
- -
- Informations pratiques
- -
- Direction de travaux des étudiants
- -
- Réception des candidats
- -
- Pré-requis
- -
-
ENS-Ulm
75005 Paris
2nd semestre / hebdomadaire, vendredi 14:00-16:00
du 10 septembre 2021 au 14 janvier 2022