Background and activities
Group leader, Integrative Neuroscience Group, Department of Neuromedicine and Movement Science, NTNU
Secretary General and President-Elect of the Norwegian Neuroscience Society (NNS)
Member: Federation of European Neuroscience Societies (FENS); Society for Neuroscience (SfN); ALBA Network; Translational Neuroscience Clinical-Academic Group for Alzheimer´s Disease
The main research interest of our group is the study and elucidation of neuroplasticity mechanisms in the context of CNS damage and repair. Specifically, we model and investigate dynamic structure-function relationships in neuronal assemblies in healthy and perturbed conditions with the goal of identifying and engaging key aspects of complex neural network behaviour that determine adaptive or maladaptive neuroplasticity in the lesioned CNS, including injury and neurodegenerative disease.
Ongoing research activities focus on CNS lesion modelling through the integration of advanced theoretical concepts and interdisciplinary methods and tools. Apart from in vivo models, we work with in vitro and computational models that recapitulate and exploit fundamental attributes of biological neural networks, including self-organization over time into assemblies of increasing structural complexity, with concomitant emergence of complex functional dynamics.
Our working hypotheses are based on the relevance of specific identifiable network topologies as well as patterns of synaptic transmission for the functional capacity of a network in terms of plasticity, learning, and adaptability and, by the same token, for the initiation and spread of lesion-related pathologies in vivo and in vitro.
These research activities are coupled to clinical research by our group investigating dynamic neuroplasticity using connectomics and transcriptional analyses.
Selected publications 2018-date
Scientific, academic and artistic work
Displaying a selection of activities. See all publications in the database
- (2021) Tapping into the aging brain: In vivo Microdialysis reveals mirroring pathology between preclinical models and patients with Alzheimer's disease. BioRxiv.
- (2021) Criticality, connectivity, and neural disorder: A multifaceted approach to neural computation. Frontiers in Computational Neuroscience. vol. 15:611183.
- (2021) Hallmarks of Criticality in Neuronal Networks Depend on Cell Type and the Temporal Resolution of Neuronal Avalanches. International Journal of Unconventional Computing. vol. 16 (4).
- (2021) Bayesian supervised machine learning classification of neural networks with pathological perturbations. Biomedical Engineering & Physics Express.
- (2021) Early functional changes associated with alpha-synuclein proteinopathy in engineered human neural networks. American Journal of Physiology - Cell Physiology. vol. 320 (6).
- (2020) Bridging the gap between fluid biomarkers for Alzheimer’s disease, model systems, and patients. Frontiers in Aging Neuroscience. vol. 12.
- (2020) Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches. Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI2019).
- (2020) Method to Obtain Neuromorphic Reservoir Networks from Images of in Vitro Cortical Networks. Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI2019).
- (2020) A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality. Cognitive Neurodynamics.
- (2020) EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality. Applications of Evolutionary Computation.
- (2020) Criticality as a measure of developing proteinopathy in engineered human neural networks. BioRxiv.
- (2020) Structural and functional alterations associated with the LRRK2 G2019S mutation revealed in structured human neural networks. BioRxiv.
- (2019) Modelling functional human neuromuscular junctions in a differentially-perturbable microfluidic environment, validated through recombinant monosynaptic pseudotyped ΔG-rabies virus tracing. BioRxiv.
- (2019) Connectomics of morphogenetically engineered neurons as a predictor of functional integration in the ischemic brain. Frontiers in Neurology. vol. 10.
- (2019) Formation of neural networks with structural and functional features consistent with small-world network topology on surface-grafted polymer particles. Royal Society Open Science. vol. 6 (10).
- (2019) A novel lab-on-chip platform enabling axotomy and neuromodulation in a multi-nodal network. Biosensors & bioelectronics. vol. 140:111329.