A spiking working memory model based on Hebbian short-term potentiation

F Fiebig, A Lansner - Journal of Neuroscience, 2017 - Soc Neuroscience
A dominant theory of working memory (WM), referred to as the persistent activity hypothesis,
holds that recurrently connected neural networks, presumably located in the prefrontal …

Learning multiple variable-speed sequences in striatum via cortical tutoring

JM Murray, GS Escola - Elife, 2017 - elifesciences.org
Sparse, sequential patterns of neural activity have been observed in numerous brain areas
during timekeeping and motor sequence tasks. Inspired by such observations, we construct …

Learning spatiotemporal signals using a recurrent spiking network that discretizes time

A Maes, M Barahona, C Clopath - PLoS computational biology, 2020 - journals.plos.org
Learning to produce spatiotemporal sequences is a common task that the brain has to solve.
The same neurons may be used to produce different sequential behaviours. The way the …

The impact of spike timing precision and spike emission reliability on decoding accuracy

W Nicola, TR Newton, C Clopath - Scientific Reports, 2024 - nature.com
Precisely timed and reliably emitted spikes are hypothesized to serve multiple functions,
including improving the accuracy and reproducibility of encoding stimuli, memories, or …

Characteristics of sequential activity in networks with temporally asymmetric Hebbian learning

M Gillett, U Pereira, N Brunel - Proceedings of the National …, 2020 - National Acad Sciences
Sequential activity has been observed in multiple neuronal circuits across species, neural
structures, and behaviors. It has been hypothesized that sequences could arise from …

Learning precise spatiotemporal sequences via biophysically realistic learning rules in a modular, spiking network

I Cone, HZ Shouval - Elife, 2021 - elifesciences.org
Multiple brain regions are able to learn and express temporal sequences, and this
functionality is an essential component of learning and memory. We propose a substrate for …

Dendrites, deep learning, and sequences in the hippocampus

US Bhalla - Hippocampus, 2019 - Wiley Online Library
The hippocampus places us both in time and space. It does so over remarkably large spans:
milliseconds to years, and centimeters to kilometers. This works for sensory representations …

Sequence learning, prediction, and replay in networks of spiking neurons

Y Bouhadjar, DJ Wouters, M Diesmann… - PLOS Computational …, 2022 - journals.plos.org
Sequence learning, prediction and replay have been proposed to constitute the universal
computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) …

An indexing theory for working memory based on fast hebbian plasticity

F Fiebig, P Herman, A Lansner - eneuro, 2020 - eneuro.org
Working memory (WM) is a key component of human memory and cognition. Computational
models have been used to study the underlying neural mechanisms, but neglected the …

Scalable Multi-FPGA HPC Architecture for Associative Memory System

D Wang, X Yan, Y Yang, D Stathis… - … Circuits and Systems, 2024 - ieeexplore.ieee.org
Associative memory is a cornerstone of cognitive intelligence within the human brain. The
Bayesian confidence propagation neural network (BCPNN), a cortex-inspired model with …