Random processes in the brain: From experimental data to Math and back

27 févr. 2023, 08:00 → 7 avr. 2023, 21:00 Europe/Paris

Amphitheater Darboux (IHP)

Thematic scientific program at Institut Henri Poincaré, Paris

Random processes in the brain: From experimental data to Math and back

February 27th to  April 7th, 2023

 

Back to the thematic main page.

 

Short Program 

1st week: February 27-March 3: Scratch courses from March 1 to March 3:

C.Pouzat, E.Löcherbach, C.D Vargas,  A. Duarté

2nd week: March 6 to March 10: Workshop: Structural learning by the brain

 

3rd week: March 13 to March 17:  Doctoral course: Structural learning by the brain

C. D. Vargas, A. Duarte, M. Svarc  

4th week: March 20-24: Doctoral course: Stochastic modelling of neural networks

A. Galves, C. Pouzat  

5th week: March 27-March 31: Workshop: Networks of spiking neurons

 

6th week: April3-April 7: Hands-on week: Doctoral courses and discussion of projects with student

 

More information can be found here

Detailed program hehttps://indico.math.cnrs.fr/event/7792/attachments/3752/5391/RPB-IHP-Dec-15.pdfre

About the NeuroMat Project

Guidelines for the poster session

Organizers:

Antonio Galves (Universidade de São Paulo, galves@usp.br)

Eva Löcherbach (Paris 1 Panthéon-Sorbonne, eva.locherbach@univ-paris1.fr)

Christophe Pouzat (CNRS Université de Strasbourg, christophe.pouzat@math.unistra.fr)

Claudia D. Vargas ( Universidade Federal de Rio de Janeiro)

You will also need to register for the conferences you wish to attend via the dedicated registration form(s)

 

Doc_cours_Stoch_modelling.pdf

Networks of spiking neurons_21.03.pdf

Programmecolloquemars2023.pdf

RPB-IHP-21. 03.pdf

Scratch courses.pdf

séance grand publique.pdf

Workshop_structural _learning-1.pdf

Workshop_structural-_learning-2.pdf

Workshop_structural-_learning_7.03.pdf

mercredi 1 mars

1 Neurobiology for mathematicians by C. Pouzat with F. Najman, P. Passos, B. Ramalho

Content: Primer on basic neural physiology for mathematicians; von
Helmholtz's conjecture of the predictive brain; intrinsic variability
of neurobiological data and the need of probabilistic models

2 Stochastics for neurobiologists by A. Duarte and E. Löcherbach

Content: Stochastic chains: Markov chains and variable length
models; a simple model for spiking neurons and statistical
inference; modeling EEG data.

3 Informal discussions and project proposals / discussions with younger researchers.

jeudi 2 mars

4 Neurobiology for mathematicians by C. Pouzat with F. Najman, P. Passos, B. Ramalho

Content: Primer on basic neural physiology for mathematicians; von
Helmholtz's conjecture of the predictive brain; intrinsic variability
of neurobiological data and the need of probabilistic models

5 Stochastics for neurobiologists by A. Duarte and E. Löcherbach

Content: Stochastic chains: Markov chains and variable length
models; a simple model for spiking neurons and statistical
inference; modeling EEG data.

6 Informal discussions and project proposals / discussions with younger researchers

vendredi 3 mars

7 Neurobiology for mathematicians by C. Pouzat with F. Najman, P. Passos, B. Ramalho

Content: Primer on basic neural physiology for mathematicians; von
Helmholtz's conjecture of the predictive brain; intrinsic variability
of neurobiological data and the need of probabilistic models

8 Stochastics for neurobiologists by A. Duarte and E. Löcherbach

Content: Stochastic chains: Markov chains and variable length
models; a simple model for spiking neurons and statistical
inference; modeling EEG data.

9 Informal discussions and project proposals / discussions with younger researchers.

lundi 6 mars

10 Workshop : Structural learning by the brain: Welcome coffee

11 Olivier Faugeras: Mathematical neuroscience

12 Coffee break

13 Risto Ilmoniemi: Randomness in the brain: TMS versus sensory stimulation

14 Group photo

15 Présentation de l'équipe de l'IHP par directeur adjoint de l'IHP Pr. Dominique Mouhanna

16 Florent Meyniel: Is human statistical learning Bayesian?

17 Coffee break

18 Sonja Gruen: Higher-order spike patterns in cortex and models

mercredi 8 mars

19 Leonardo Cohen: Consolidation of human skill linked to waking hippocampo-neocortical replay

20 Coffee break

21 Vikram Chib: Subjective valuation of effort.

22 Claudia D. Vargas: The goal-keeper game: predicting upcoming events by the brain.

23 Coffee break

24 Bill Lytton: Avalanches in primary motor cortex

jeudi 9 mars

25 Aline Duarte: Retrieving context trees from EEG data

26 Coffee break

27 Daniel Fraiman: An ANOVA approach for statistical comparisons of brain networks

28 Oswaldo Baffa: Retrieving context tree models driven by structured TMS pulse sequences

29 Coffee break

30 Viktor Jirsa, The Virtual Brain in Applications to Medicine

31 Cocktail and poster session with a short oral introduction: Fernando Najman, Paulo Passos, Bia Ramalho, Victor Hugo Souza, Noslen Hern\'andez, Renan Shimoura, Raquel Carvalho

vendredi 10 mars

32 Marcela Svarc: EEG clustering and data compression by the brain

33 Coffee break

34 Maria Elisa Pimentel, Raphael Stern : The Goalkeeper Game: A new assessment tool for prediction of gait performance under complex condition in people with Parkinson's disease

35 Antoine Triller: Synaptic receptors mouvement and brain diseases.

36 Coffee break

37 Yves Frégnac: Beyond the Metaphor between the digital Computer and the biological brain : the myth of artificial consciousness

lundi 13 mars

38 Coffee break

39 1st Doctoral course: Structural-learning-by-the-brain by C. Vargas, A. Duarte, M. Svarc.

Content: Learning stochastic sequences of events by the brain; sequences of random objects driven by context tree models; statistical model selection for sequences of random objects driven by context tree models; the projective method; evoked potentials in EEG data; retrieving the structure of probabilistic sequences from EEG data; clustering EEG data by law.

40 Coffee and informal discussions

mardi 14 mars

41 Coffee break

42 1st Doctoral course: Structural learning by the brain. by C. Vargas, A. Duarte, M. Svarc

Content: Learning stochastic sequences of events by the brain; sequences of random objects driven by context tree models; statistical model selection for sequences of random objects driven by context tree models; the projective method; evoked potentials in EEG data; retrieving the structure of probabilistic sequences from EEG data; clustering EEG data by law.

43 Coffee and informal discussions

44 Séance grand public :Olivier Faugeras: Des mathéematiques au chevet des neurones et des astrocytes

45 Séance grand public: Gilles Laurent: Evolution, Fonctions et Dynamique du Cerveau.

mercredi 15 mars

46 Coffee break

47 1st Doctoral course: Structural learning by the brain. C. Vargas, A. Duarte, M. Svarc

Learning stochastic sequences of events by the brain; sequences of random objects driven by context tree models; statistical model selection for sequences of random objects driven by context tree models; the projective method; evoked potentials in EEG data; retrieving the structure of probabilistic sequences from EEG data; clustering EEG data by law.

48 Coffee and informal discussions

jeudi 16 mars

49 Coffee break

50 1st Doctoral course: Structural learning by the brain. C. Vargas, A. Duarte, M. Svarc

Content: Learning stochastic sequences of events by the brain; sequences of random objects driven by context tree models; statistical model selection for sequences of random objects driven by context tree models; the projective method; evoked potentials in EEG data; retrieving the structure of probabilistic sequences from EEG data; clustering EEG data by law.

51 Coffee and informal discussions

52 André Frazão Helene: Imagery and actual execution of sequential motor tasks

vendredi 17 mars

53 Coffee break

54 1st Doctoral course: Structural learning by the brain. C. Vargas, A. Duarte, M. Svarc

Content: Learning stochastic sequences of events by the brain; sequences of random objects driven by context tree models; statistical model selection for sequences of random objects driven by context tree models; the projective method; evoked potentials in EEG data; retrieving the structure of probabilistic sequences from EEG data; clustering EEG data by law.

55 Christophe Pouzat: Where data come from and what do we model?

56 Gilles Laurent: Exploring the space of neural systems dynamics

57 Coffee break

lundi 20 mars

58 Coffee break

59 2nd Doctoral course: Stochastic modeling of neural networks. by A. Galves and C. Pouzat. Lecture.

60 Coffee and informal discussions

61 Work in progress seminar: Erin Schuman (MPI)

mardi 21 mars

62 Coffee break

63 2nd Doctoral course: Stochastic modeling of neural networks. by A. Galves and C. Pouzat. Lecture.

64 Coffee and informal discussions

mercredi 22 mars

65 Coffee break

66 2nd Doctoral course: Stochastic modeling of neural networks. by A. Galves and C. Pouzat. Lecture.

67 Coffee and informal discussions

68 Work in progress seminar: Dasha Loukianova (Evry)

jeudi 23 mars

69 Coffee break

70 2nd Doctoral course: Stochastic modeling of neural networks. by A. Galves and C. Pouzat. Lecture.

71 Coffee and informal discussions

72 Work in progress seminar

vendredi 24 mars

73 Coffee break

74 2nd Doctoral course: Stochastic modeling of neural networks. by A. Galves and C. Pouzat. Lecture.

75 Coffee and informal discussions

76 Work in progress seminar: Michel Davydov (INRIA Paris)

77 Work in progress seminar : Julien Aubert (Nice)

78 Work in progress seminar : Sophie Jaffard (Nice)

lundi 27 mars

79 Workshop: Networks of spiking neurons. Welcome coffee

80 Markus Diesmann: Simulation of large-scale neural networks.

81 Coffee break

82 Sacha van Albada, From structure to activity and back in spiking cortical models

83 Group photo

84 Ryota Kobayashi, Network inference from time series

85 Coffee break

86 Shigeru Shinomoto : Searching for neuronal activities involving behavioral changes in animals

mercredi 29 mars

87 Bruno Cessac: A dynamical system point of view

88 Coffee break

89 Massimiliano Tamborrino: ABC for neuronal data

90 Rodrigo Cofré:Scalable and accurate method for neuronal ensemble detection in spiking neural networks

91 Priscilla Greenwood: Building a stochastic neural circuit of cortical-pulvinar interaction

92 Coffee break

93 Mauro Piccioni and Emilio De Santis: Statistical model selection in the class of systems of interacting point processes with memory of variable length

94 Cocktail and poster session with a short oral introduction: Morgan André, Kadmo de Souza Laxa, Valentin Schmutz, Zoé Agathe-Nerine, Nadia Belmabrouk, Marie Levakova, Francesca Cavallini, Michel Davydov, Flavio Rusch, Nils Eric Greven

jeudi 30 mars

95 Thibaud Taillefumier, Replica-mean field limits of metastable dynamics

96 Coffee break

97 Tilo Schwalger : Mesoscopic description of metastability in spiking neural networks

98 Antonio C. Roque: Spontaneous activity patterns in networks of nonlinear two-dimensional integrate and fire neurons.

99 Etienne Tanré, Spatial and temporal correlations in spikes trains: adaptation or noise with memory?

100 coffee break

101 Reinhard Höpfner: On circuits of stochastic Hodgkin-Huxley neurons

vendredi 31 mars

102 Céline Duval, Recent results on Hawkes processes.

103 Coffee break

104 Guilherme Ost, Neural Coding as a Statistical Testing Problem

105 Gilles Louppe: Simulation based network inference.

106 Romain Veltz, Theoretical/numerical study of modulated traveling pulses in inhibition stabilized networks

107 Coffee break

108 Patricia Reynaud-Bouret, Encoding/decoding abilities of the DMS and DLS networks during learning

mardi 4 avril

109 Eva Löcherbach. Doctoral course: Perfect simulation of systems of interacting neurons.