Publications

Publication Highlights

  1. Jørgen Jensen Farner, Ola Huse Ramstad, Stefano Nichele, Kristine Heiney (2022). “Local learning through propagation delays in spiking neural networks.” Accepted: Local Learning Workshop, International Conference on Machine Learning (ICML) 2023.

Taking inspiration from observations that the transmission speed of action potentials may vary in response to activity levels, we designed a local delay learning rule for spiking neural network models. The goal of this method is to align the arrival of presynaptic spikes to evoke a stronger and faster postsynaptic response. We show that this method can be used to train spiking neural networks to classify handwritten digits, and that this approach to learning can allow networks to generalize to unseen inputs.
This paper represents my first time as main supervisor of a master thesis project. I conceived of the study and guided the first author in his development and implementation of the computational models and algorithms.

  1. Kristine Heiney, Ola Huse Ramstad, Ioanna Sandvig, Axel Sandvig, Stefano Nichele (2019). “Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches.” Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI2019). Chapter: Artificial Life (ALIFE). pp. 246-253.

It has been theorised that the cortex may self-organise at or near the critical state to optimize its computational capacity; however, neuronal cultures frequently do not show features of this state as they mature, instead producing activity patterns that overwhelm the network. In this study, we chemically manipulated neuronal cultures to show hallmarks of criticality by increasing inhibition in the network. Studying these systems before and after intervention can give insights into how criticality may support neural computation.

  1. Jørgen Jensen Farner, Håkon Weydahl, Ruben Jahren, Ola Huse Ramstad, Stefano Nichele, Kristine Heiney (2021). “Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity.” Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI2021). Chapter: International Conference on Evolvable Systems (ICES).
    2021 IEEE Brain Best Paper Award Runner Up
    Media coverage

We designed model systems of spiking neurons to exhibit activity similar to that observed in vitro (data from Wagenaar, Pine & Potter, BMC Neuroscience, 2006). Using evolutionary algorithms, we were able to produce complex activity with fairly simple homogenous systems of spiking neurons. Such models can both help elucidate features of biological neurons and contribute to more efficient artificial intelligence models.
This study grew out of a student project in a master course (Evolutionary Artificial Intelligence and Robotics, ACIT4610, OsloMet). I conceived of the project idea for the course and acted as main supervisor of the master students during both the course and the subsequent expansion of the project.

  1. Kristine Heiney, José C. Mateus, Cátia D.F. Lopes, Estrela Neto, Meriem Lamghari, Paulo Aguiar (2019). “µSpikeHunter: An advanced computational tool for the analysis of neuronal communication and action potential propagation in microfluidic platforms.” Scientific Reports 9, 5777.

This paper showcases the computational tool I developed during my master thesis work at the Institute for Research and Innovation in Health (i3S). This tool allows users to study spike propagation and inter-population communication, using electrophysiological data collected from microelectrode arrays interfaced with microfluidic chambers, without requiring any programming skills. I implemented this tool in MATLAB and developed the all of the analytical functions. The tool’s capabilities include robust detection of propagating spikes, multiple estimates for propagation velocity, and graphical spike sorting.

  1. Kristine Heiney, Ola Huse Ramstad, Vegard Fiskum, Nicholas Christiansen, Axel Sandvig, Stefano Nichele, Ioanna Sandvig (2021). “Criticality, Connectivity, and Neural Disorder: A Multifaceted Approach to Neural Computation.” Frontiers in Computational Neuroscience 15.

This review paper delves into the relationship between the avalanche dynamics and functional connectivity of neuronal networks. How a system propagates activity is closely intertwined with how its elements are connected to one another, and we propose complementing studies of criticality with investigations into the connectivity of the target networks.

Complete Publication List

  1. Alessandro Pierro, Kristine Heiney, Shamit Shrivastava, Giulia Marcucci, Stefano Nichele (2023). “Optimization of a hydrodynamic computational reservoir through evolution.” The Genetic and Evolutionary Computation Conference (GECCO) 2023.

  2. Jørgen Jensen Farner, Ola Huse Ramstad, Stefano Nichele, Kristine Heiney (2022). “Local learning through propagation delays in spiking neural networks.” Accepted: Local Learning Workshop, International Conference on Machine Learning (ICML) 2023.

  3. Kristine Heiney, Ola Huse Ramstad, Vegard Fiskum, Axel Sandvig, Ioanna Sandvig, Stefano Nichele (2022). “Neuronal avalanche dynamics and functional connectivity elucidate information propagation in vitro.” Frontiers in Neural Circuits 16.

  4. Jørgen Jensen Farner, Håkon Weydahl, Ruben Jahren, Ola Huse Ramstad, Stefano Nichele, Kristine Heiney (2021). “Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity.” Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI2021). Chapter: International Conference on Evolvable Systems (ICES).
    2021 IEEE Brain Best Paper Award Runner Up
    Media coverage

  5. Kristine Heiney, Ola Huse Ramstad, Vegard Fiskum, Nicholas Christiansen, Axel Sandvig, Stefano Nichele, Ioanna Sandvig (2021). “Criticality, Connectivity, and Neural Disorder: A Multifaceted Approach to Neural Computation.” Frontiers in Computational Neuroscience 15.

  6. Vibeke Devold Valderhaug, Kristine Heiney, Ola Huse Ramstad, Geir Bråthen, Wei-Ling Kuan, Stefano Nichele, Axel Sandvig, Ioanna Sandvig, (2021): “Early functional changes associated with alpha-synuclein proteinopathy in engineered human neural networks.” American Journal of Physiology - Cell Physiology 320(6).

  7. Kristine Heiney, Vibeke Devold Valderhaug, Ola Huse Ramstad, Ioanna Sandvig, Axel Sandvig, Stefano Nichele (2021). “Hallmarks of Criticality in Neuronal Networks Depend on Cell Type and the Temporal Resolution of Neuronal Avalanches.” International Journal of Unconventional Computing 16(4).

  8. Vibeke Devold Valderhaug, Ola Huse Ramstad, Rosanne van de Wijdeven, Kristine Heiney, Stefano Nichele, Axel Sandvig, Ioanna Sandvig (2020). “Structural and functional alterations associated with the LRRK2 G2019S mutation revealed in structured human neural networks.” bioRxiv.

  9. Kristine Heiney, Gunnar Tufte, Stefano Nichele (2020). “On artificial life and emergent computation in physical substrates.” arXiv.

  10. Kristine Heiney, Ola Huse Ramstad, Ioanna Sandvig, Axel Sandvig, Stefano Nichele (2019). “Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches.” Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI2019). Chapter: Artificial Life (ALIFE). pp. 246-253.

  11. Kristine Heiney, José C. Mateus, Cátia D.F. Lopes, Estrela Neto, Meriem Lamghari, Paulo Aguiar (2019). “µSpikeHunter: An advanced computational tool for the analysis of neuronal communication and action potential propagation in microfluidic platforms.” Scientific Reports 9, 5777.