most citedEvaluation of the criticality of in vitro neuronal networks: Toward an assessment of computational capacity

3 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.NC2024★ 1 cited

Information encoding and decoding in in-vitro neural networks on micro electrode arrays through stimulation timing

Trym A. E. Lindell, Ola H. Ramstad, Ionna Sandvig +2

A primary challenge in utilizing in-vitro biological neural networks for computations is finding good encoding and decoding schemes for inputting and decoding data to and from the…

q-bio.NC2019

Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches

Kristine Heiney, Ola Huse Ramstad, Ioanna Sandvig +2

In this work, we report the preliminary analysis of the electrophysiological behavior of in vitro neuronal networks to identify when the networks are in a critical state based on t…

q-bio.NC2019★ 3 cited

Evaluation of the criticality of in vitro neuronal networks: Toward an assessment of computational capacity

Kristine Heiney, Vibeke Devold Valderhaug, Ioanna Sandvig +4

Novel computing hardwares are necessary to keep up with today's increasing demand for data storage and processing power. In this research project, we turn to the brain for inspirat…

cs.NE2019★ 1 cited

A general representation of dynamical systems for reservoir computing

Sidney Pontes-Filho, Anis Yazidi, Jianhua Zhang +5

Dynamical systems are capable of performing computation in a reservoir computing paradigm. This paper presents a general representation of these systems as an artificial neural net…

cs.CV2019★ 1 cited

DeepTEGINN: Deep Learning Based Tools to Extract Graphs from Images of Neural Networks

Gustavo Borges Moreno e Mello, Vibeke Devold Valderhaug, Sidney Pontes-Filho +3

In the brain, the structure of a network of neurons defines how these neurons implement the computations that underlie the mind and the behavior of animals and humans. Provided tha…