CINPLA Research

CINPLA projects

• BRAINMATRIX - Multi-scale brain plasticity: From molecules to behaviour in life-long learning
• COBRA - Computing Brain Signals: Biophysical computations of electrical and magnetic brain signals
• DIGIBRAIN - Digital Brain: From genes to brain function in health and disease
• How dementia disrupts neuronal activity and memory recall

• Bio-inspired artificial intelligence

 Affiliated projects

• HBP - Human Brain Project
• 4MENT - MultiModal Mental Models: Converging approaches from genomes to mental illness and interplay with psychosocial stressors
• SUURPh - Simula-UiO-UCSD Research and PhD Training Collaboration

BrainMatrix - Multi-scale brain plasticity: From molecules to behaviour in life-long learning

The overall goal of BrainMatrix is to link molecular mechanisms with systems-level behaviour. More specifically, we study how postnatal activity-dependent plasticity can refine neural networks. To do so, we develop computational models spanning different temporal and spatial scales. The models are based on data from experimental recordings within the BrainMatrix consortium and supplemented with data from the EU Human Brain Project, Project MindScope (Allen Brain Institute), as well as other projects headed by consortium members. We use the models to make predictions, which we then test empirically using targeted experiments.

In ongoing experiments, we are using state of the art methods to characterize the structure and composition of extracellular matrix molecules that are involved in the regulation of plasticity and learning. Further, we map the contribution of these molecules to single-cell and network activity using in vitro and in vivo electrophysiological recordings and in vivo imaging, as well as the contribution to animal behaviour.

COBRA - Computing Brain Signals: Biophysical computations of electrical and magnetic brain signals

The primary goal of COBRA is to develop reliable computational models and tools for interpreting electrical and magnetic brain signal measurements. We also explore how such data can be used in large-scale network simulations and analysis tools. To do this, we use biologically detailed neuron models to calculate the contributions of cortical neuron populations to the electric and magnetic signals measured in LFP, EEG, ECoG, and MEG*. Using this approach, we explore how brain signals depend on the state and properties of cortical networks and neurons. We also develop a Python software package (CoBraPy) for use in large-scale network simulations and analysis tools. Together with various collaborators, including the EU Human Brain Project and Project MindScope (Allen Brain Institute), we compare the results from COBRA with experimental data from mice and humans.

You can read more about COBRA in this article.

DigiBrain - Digital Brain: From genes to brain function in health and disease

The goal of DigiBrain is to establish a pipeline for linking genetic information (e.g., gene variants linked to Schizophrenia) to systems-level measures of brain behaviour (e.g., EEG) in order to understand the mechanisms underlying brain diseases. To do this, we conduct multiscale computational modelling and targeted experimental animal studies at the levels of neurons, neural networks, and systems. We also investigate how behaviour can be influenced by means of specially designed drugs. The project is part of the Centre for Digital life Norway and brings together researchers from both academia and industry.

You can find more information about DigiBrain here.

How dementia disrupts neuronal activity and memory recall

This research project focuses on how neuronal activity is affected in an animal model of dementia and the correlation between activity and learning and memory.​ The project will utilize two-photon microscopy to image neuronal activity in awake, moving animals. Imaging will be done during a learning paradigm where visual stimuli presented on a screen in front of the animal is paired with either a tail shock or a reward. The goal is to link memory impairment with neuronal activity as neurodegeneration progresses.​ Furthermore, we will attempt to improve learning ability in tau pathology mice by removing perineuronal nets (PNNs) to create a plastic network.​

The project is funded by The Norwegian Health Association (Nasjonalforeningen for folkehelsen).

Bio-inspired artificial intelligence

The goal of this project is to utilise modern findings in experimental and theoretical neuroscience to improve artificial intelligence (AI). While artificial neural networks have been inspired by biological neural networks, artificial neural networks are significantly different from biology. We aim to infuse AI with biology once again, taking advantage of robustness, flexibility and transferability of biological neural networks and learning, and try to solve current problems in AI with concepts from biology.

You can find more information about the project here.

HBP - Human Brain Project: European research infrastructure to decode the human brain

The EU Human Brain Project (HBP) is a large European brain research project aiming to advance neuroscience, medicine, and brain-inspired technology. The use of methods from mathematics, computer science, and physics is central.

Six ICT research platforms form the heart of the HBP infrastructure: (1) Neuroinformatics, (2) Brain simulation, (3) High-performance analytics and computing, (4) Medical informatics, (5) Neuromorphic computing, and (6) Neurorobotics. The HBP also performs targeted research and theoretical studies and explores brain structure and function in humans, rodents, and other species. In addition, the project studies the ethical and societal implications of HBP’s work.

CINPLA researchers are particularly engaged in the Brain simulation research platform.

You can find more information about HBP on their webpage.

4MENT - MultiModal Mental Models: Converging approaches from genomes to mental illness and interplay with psychosocial stressors

4MENT is an interdisciplinary project within UiO, funded by the Convergence environments of UiO:Life Science. Many of the partners of the Digibrain project (Prof. Andreassen, Prof. Einevoll, Prof. Fyhn, and Prof. Djurovic) are also part of the 4MENT project. The goal of 4MENT is, building upon the knowledge obtained in the Digibrain project, to better understand the etiology of severe mental disorders. To achieve this, we use brain imaging and large-scale data mining integrated with psychology and philosophy, in addition to the methods of statistical genetics, electrophysiology and modelling as equipped in the Digibrain project.

You can read more about 4MENT here.