Neurocomputational mechanisms of memory – Hebbian plasticity across short and long timescales
Time: Mon 2025-06-09 10.00
Location: F2, Lindstedtsvägen 26 & 28, Stockholm
Language: English
Subject area: Computer Science
Doctoral student: Doctoral student Nikolaos Chrysanthidis , Beräkningsvetenskap och beräkningsteknik (CST)
Opponent: Professor Claudia Clopath, Imperial College London, London, UK
Supervisor: Associate Professor Pawel Herman, Beräkningsvetenskap och beräkningsteknik (CST); Professor Anders Lansner, Beräkningsvetenskap och beräkningsteknik (CST)
QC 20250509
Abstract
The mammalian brain is a complex structure, capable of processing sensory stimuli through the lens of prior knowledge and experiences to guide behavior and decision-making. This process relies on intricate neural dynamics, synaptic plasticity mechanisms, and interactions across brain networks. Despite the brain's remarkable ability to store information, even seemingly stable memories can be modified by new experiences or forgotten over time.
In this work, we use computational modelling to investigate the mechanisms underlying memory functionality, focusing on how the brain supports short- and long-term memory processes. Our research sheds light on episodic, semantic, and working memory phenomena by employing cortical memory models integrating neural plasticity, Bayesian-Hebbian synaptic plasticity across a range of short and long timescales, together with short-term non-Hebbian mechanisms. Inspired by behavioral memory tasks and experimental evidence, we explore processes such as memory semantization — where associated episodic memories are gradually decoupled, allowing for the extraction of abstract semantic meaning. We also investigate and propose hypothetical underlying neurocomputational mechanisms of verbal omissions (memory forgetting) in odor naming tasks. Additionally, we examine the interplay between episodic memory and recency effects in immediate recall. Expanding our framework to working memory, we investigate how different plasticity mechanisms interact to enable both stability and flexibility in memory maintenance.
By bridging computational models with cognitive neuroscience, this research provides new insights into the neural and synaptic basis of memory processes.