+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Montag, 16. Juni 2025, 15.00 Uhr Ort: Raum 9222, Gebäude E3, Informatik-Zentrum Referent: Tobias Schulte to Brinke, MSc. Lehrstuhl Informatik 3 Thema: Analysis of Information Processing and Memory Prerequisites for Temporal Difference Learning in Cortical Neural Network Models Abstract: This doctoral thesis delves into the computational intricacies of the human brain, exploring the capabilities of cortical microcircuit models, the extent of their information processing capacity, and their role in memory and temporal difference learning through the use of cortico-striatal populations. Central to this exploration is the study of spiking neural networks (SNN). This research aims to gain a deeper understanding of the structural and neuronal influences on information processing in these networks and at the same time to provide a guideline for their analysis. In the first part, a network model of a cortical column introduced in a previous paper is reproduced and extended. These analyses show that the specific, data-based connectivity improves computational performance by sharpening the clarity of internal representations rather than increasing the duration of information retention as previously described. Moving beyond traditional task-based evaluations, the second part introduces a novel application of the information processing capacity (IPC) metric to SNN. This approach provides a comprehensive profile of the functions computed by SNN, encompassing memory and nonlinear processing. The study methodically examines various encoding mechanisms and their impact on the IPC and shows that the metric is indicative of the performance in tasks with different demands of nonlinear processing and memory. This exploration not only extends the utility of the IPC metric to more complex neural networks but also offers a deeper insight into their computational capabilities. The third part of the thesis tests a hypothesis about the computation of temporal difference errors in the brain, focusing on two distinct populations of cortical layer 5 neurons: the crossed corticostriatal (CCS) and corticopontine (CPn0 cells. By implementing network models based on these populations and evaluating their memory capabilities through the lens of the IPC, the research supports, at least for continuous rate networks, the proposed role of these neurons in the computation of temporal difference errors. However, the spiking network models pose a greater challenge and exhibit little ability to memorize previous inputs in our experiments. In summary, this work not only confirms and extends existing research results, but also develops new methods for analyzing SNN. It lays a solid foundation for future studies of the brain's computational processes and enriches the field of computational neuroscience with advanced tools and methods for exploring the intricate workings of biologically inspired neural network models. Es laden ein: die Dozentinnen und Dozenten der Informatik -- Prof. Dr. Abigail Morrison Institute for Advanced Simulation (IAS-6) Jülich Research Center & Computer Science 3 - Software Engineering RWTH Aachen http://www.fz-juelich.de/inm/inm-6 http://www.se-rwth.de Office: +49 2428 8097504 Fax # : +49 2461 61-9460 Pronouns: she/her ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Jülich GmbH 52425 Jülich Sitz der Gesellschaft: Jülich Eingetragen im Handelsregister des Amtsgerichts Düren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Stefan Müller Geschäftsführung: Prof. Dr. Astrid Lambrecht (Vorsitzende), Dr. Stephanie Bauer (stellv. Vorsitzende), Prof. Dr. Ir. Pieter Jansens, Prof. Dr. Laurens Kuipers ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------