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Nikolaos Chrysanthidis

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About me


I am a PhD student in Prof. Herman’s lab at KTH's School of Electrical and Computer Engineering in Stockholm. I hold a BSc and MSc in Electrical and Computer Engineering at the Aristotle Univeristy, in Greece. During my graduate studies, I have conducted research at TU Delft with prof. Koen Bertels in a machine learning project using artificial neural networks.

My current research focuses on hypotheses revolving around computational and cognitive neuroscience, employing spiking neural networks, and non-spiking network models. Over the past years, I have developed large-scale models of cortical networks with a focus on bridging the gap between brain function and the underlying mesoscopic-level biological processes.

We aim to provide a mechanistic explanation of memory phenomena concerning episodic, semantic, and working memory in continual learning paradigms. Recently, we investigated the sanitization of episodic memories, often described as the decontextualization of  associative memories - decoupling items from their associated contextual information.

Further ongoing projects focus on understanding and exploring the interplay between short-term dynamics (i.e., effects of recency) and long-term episodic memory processes on remembering item-in-contexts (episodic item-in-context memory).

Also, using non-spiking models, we are exploring the mechanisms that lead to episodic memory forgetting and omission (blank response) in an olfactory memory task. Our models integrate various plasticity mechanisms at multiple time scales, coexisting and interacting to contribute to function and behavior.

We also study the synergistic interaction of these learning rules in a suite of different working memory tasks and report the role and contribution of each plasticity mechanism in recall.



Artificial Neural Networks and Deep Architectures (DD2437), assistant | Course web

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