Keynote & Tutorial
Keynote: Thursday, August 14, 1:45 - 3:45 pm, Room TBA
Tutorial: Thursday, August 14, 4:15 - 6:00 pm, Room TBA
Digital Brain Models for Working Memory
Jorge Mejias1, Francisco Pascoa dos Santos1, Parva Alavian1, Rares Dorcioman1; 1University of Amsterdam
Abstract
Digital brain models, or whole-brain models, are able to incorporate part of the complex brain connectivity obtained from neuroimaging scans, and are usually used to replicate brain activity dynamics. Their capacity to explain even basic cognitive properties is, however, extremely limited. In this keynote, we will present recent advances in which digital brain model are built to incorporate basic capabilities to perform working memory tasks. These models are biophysically oriented and constitute a proof of concept to be expanded in future studies towards more computationally powerful implementations. We will cover examples of models for the human and macaque brains, exploring how these models illustrate a paradigm shift in working memory: from considering it a local process occurring only in prefrontal cortex, to a distributed mechanism which involves multiple cooperating regions across large portions of the brain. We will highlight existing experimental evidence for this new paradigm as well as testable predictions for experimental neuroscientists.
Tutorial Outline
The goal of this tutorial is to replicate the main results of distributed working memory models (as presented in Mejias and Wang, eLife 2022) to gain a better and hands-on understanding of the distributed working memory theory (Christophel et al. TiCS 2017). The tutorial’s ideal audience are computational neuroscience researchers (Master, PhD, postdoc, professors) interested in how cognitive functions could be embedded in biologically realistic brain networks.
We will start the tutorial by focusing on the basic mathematical elements of the model for a single brain region, along with its relevant parameters (15 min). We will then introduce a first hands-on exercise in which attendees will simulate the dynamics of a single brain region, and gain intuition on how this model can display elevated neural firing associated with working memory (20 min). The tutorial continues with a careful overview of relevant neuroanatomical data, such as the brain connectivity (10 min) and describe how to use this data to build our digital brain model (20 min). The closing activity will be a second hands-on exercise in which attendees will simulate a full digital brain model for a simple working memory task, replicating the main result of the core article (20 min) and simulating the effect of brain lesions (15 min). The total time of the tutorial will be around 1h 35min, with plenty of time to address issues and questions along the session. The tutorial will use Python (Jupyter notebooks) and standard Python libraries like NumPy to run.