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Internationale Sommerakademie der Studienstiftung in Rot an der Rot

Arbeitsgruppe 1

Konzepte der theoretischen Neurowissenschaft: Physik trifft Gehirn

Leiter der Arbeitsgruppe

Dr. Tatjana Tchumatchenko (tatjana.tchumatchenko@brain.mpg.de), Tim Herfurth (tim.herfurth@brain.mpg.de), Marc Leonhardt (marc.leonhardt@brain.mpg.de)

Zeit

10. bis 22. August 2015

Vorträge

Die Dauer der Vorträge inklusive Diskussion: 50 Minuten Die pdf Versionen der Vorträge werden im Laufe der Akademie gesammelt und allen Teilnehmern zur Verfügung gestellt.

Organisation

Bitte emailen Sie die Vorträge im pdf Format per E-Mail an den jeweiligen Betreuer ihres Vortrages. Dabei wäre es nett, wenn Sie die Dateien Größe unter 3 MB halten und die Dateien nach dem "Nr_Titel_Nachname.pdf" Muster benennen.

Zeitplan

Tag Titel/Thema Literatur Vortragende/r Betreuer
Tag 1
(11.08.2015)		 Biologie der Neuronen und Synapsen 1, 3 JD Tim Herfurth
Tag 1 Techniken der Steuerung und Aufnahme der neuronalen Aktivität 1, 3, 7, 8 OR Tim Herfurth
Tag 2 Überblick über die Anatomie des Gehirns und speziell der Hirnrinde 1, 3, 6 MM Tim Herfurth
Tag 2 Modellbeschreibung eines Neurons 2, 4 LS Tim Herfurth
Tag 3 Synaptische Plastizität 1, 3, 10, 11 GF Tim Herfurth
Tag 3 Mean field Ansatz im neuronalen Kontext 4, 22-26 BC Marc Leonhardt
Tag 4 “Balanced Networks”: Ein Modell kortikaler Aktivität 4, 25, 27-31 YP Marc Leonhardt
Tag 4 Gruppenarbeit: Gruppe 1 (Mathematische Rechnungen), Gruppe 2 (Simulationen eines Neurons)    Alle Tatjana Tchumatchenko, Tim Herfurth, Marc Leonhardt
Tag 5 Einführung in das Hopfield Modell 14, 15, 16 TF-H Tim Herfurth
Tag 5 Ising Modell aus der Sicht der Physik 23, 24, 32 YÖ Marc Leonhardt
Tag 6 Ising Modell angewendet auf Neurowissenschaft 33-36 MG Marc Leonhardt
Tag 6 Informationstheorie: Betrachtung einzelner Neuronen 2, 5, 19, 21 GS Tim Herfurth
Tag 7 Informationstheorie in neuronalen Netzwerken 5, 18, 17, 20 RJ Tim Herfurth
Tag 7 Logische Gatter als kleinste Recheneinheit eines Computers 14, 37 PF Marc Leonhardt
Tag 8 Klassifizierung mit Hilfe des Perceptron Modells und die Rolle logischer Gatter 14, 38-42 DS Marc Leonhardt
Tag 8 Einführung in Machine Learning und Klassifikationsalgorithmen 38, 39, 41-43 FT Marc Leonhardt
Tag 9 Training von feed-forward Netzwerken am Beispiel von Backpropagation 38, 39, 41,43 GK Marc Leonhardt
Tag 9 Vorstellung und Diskussion der Anwendungen des Machine Learning 43-48 DD Marc Leonhardt
Tag 9 Diskussion und Review über alle Vorträge - Tatjana Tchumatchenko

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