Wir freuen uns sehr, drei hervorragende Sprecher*innen für die Hauptvorträge gewonnen zu haben.

Nikolai Axmacher

What we remember from an episode:
Memory as reactivation, transformation, and selection

Nikolai Axmacher
Ruhr-Universität Bochum

Experiences are stored in the brain via modifications of synaptic connections, changing the neural representations of specific events. Network-level signatures of these representations – “engram patterns” – can be extracted from patterns of EEG oscillations and fMRI BOLD activity. In the first part of my talk, I will show how reoccurrence of engram patterns supports diverse memory functions from short-term memory maintenance to long-term memory retrieval and consolidation: memory as reactivation. However, it is commonly assumed that memory is not a veridical reproduction of past experiences but involves substantial transformations. In the second part, I will describe a taxonomy of memory transformation processes and discuss some conceptual problems of a generative view on memory: memory as transformation. I will then describe a novel view which assumes that engram patterns consist of multiple representational formats which can be selectively activated during memory processes and quantitatively described via deep neural networks. Some initial evidence for this view of memory as selection is presented, together with ideas for future research.

Ulrike Lüken

Optimizing psychological treatments:
from mechanisms to predictions to clinical utility

Ulrike Lüken
Humboldt-Universität zu Berlin

Russel Poldrack

Towards a culture of computational reproducibility

Russell Poldrack
Standford University

Ensuring that the results of data analysis are both valid and reproducible is a fundamental responsibility of every computational scientist, but both are increasingly difficult in the context of complex analysis workflows and big data. Building off of ideas from software engineering, I will argue that we need to embrace a culture of computational reproducibility. I will outline a set of values that motivate this work and principles that guide the work, and then focus on a set of practices that can help improve reproducibility in computational science. I will conclude by addressing some potential concerns about the impacts of this cultural shift.