Florian Fiebig

Synergistic short-term synaptic plasticity mechanisms for working memory

This study evaluates synergistic interactions between three short-term plasticity mechanisms in spiking neural networks to enhance working memory performance across diverse tasks.

Interplay of Long- and Short-term Synaptic Plasticity in a Spiking Network Model of Rat's Episodic Memory

The paper builds a spiking network model of rat episodic memory to study how long- and short-term synaptic plasticity interact in memory tasks.

Traces of semantization - from episodic to semantic memory in a spiking cortical network model

This paper proposes a cortical spiking neural network model with Bayesian-Hebbian learning to explain semantization in episodic memory, showing it outperforms STDP in capturing decontextualization.

An Indexing Theory for Working Memory based on Fast Hebbian Plasticity

The paper proposes a WM indexing theory using a spiking neural network model to explain how PFC associates, maintains, and updates multi-modal LTM representations through fast Hebbian plasticity.

Introducing double bouquet cells into a modular cortical associative memory model

The paper introduces a biophysically plausible double bouquet cell model into a cortical microcircuit to address issues with learning rules that simultaneously learn excitation and inhibition.