Imaging neuronal circuits of the prefrontal cortex during a gambling task
Funded by: WWTF Vienna Science and Technology Fund
Duration: May 2015-April 2019
We will use Ca2+ imaging of neuronal activity to determine how distinct prefrontal cell types contribute to decisions in a modified Iowa gambling task: A rat has to choose between certain but low amounts of reward or high amounts of reward which are not delivered on every occasion. For the imaging of neuronal activity during the task performance we will use a recently developed mini-microscope that can be mounted on the skull of freely-moving rats. This microscope allows the live-imaging of Ca2+ activity of hundreds of neurons simultaneously. Furthermore, we will develop a novel mathematical method that will allow the matching of neurons between live Ca2+ imaging pictures and post-hoc histological sections. Therefore we will be able to identify the cell types of imaged neurons with histological techniques. We will determine how identified cell types and assemblies of neurons contribute to different phases of the gambling task. We will determine which information is distributed to different brain areas via different types of pyramidal cells. Also, we will determine how distinct types of GABAergic interneuron gate the neuronal cell assemblies during the different phases of the task including reward delivery, lack of reward, strategy switching and execution of a decision. Overall, this project aims at imaging the temporal activities in large neuronal assemblies of prefrontal networks and at determining how distinct types of prefrontal neuron steer the decision making process.
Georg Dorffner (co-PI)
Thomas Klausberger (PI, Center for Brain Research)
Johannes Passecker (Center for Brain Research)
Hugo Malagon (Center for Brain Research)
Multi-sensor continuous sleep modeling based on contextual data fusion
Funded by: FWF Austrian Science Fund
Duration: October 2007-September 2010
The aim of the project was to develop new algorithms and tools for the analysis of the microstructure of sleep based on biosignals such as electroencephalography (EEG), as a new form of modelling sleep overcoming the limits of classical sleep staging.
The project resulted in the development of a probabilistic sleep model (PSM) with high spatial and temporal resolution, validated on a large data base of several hundred polysomnographic (OSG) recordings. It could be proven that such models contain more information about human sleep in that their main characteristics have a significantly higher correlation with outside criteria such as subjective sleep quality than variables from sleep staging. It could also be demonstrated that sleep EEG has characteristic individual properties across subjects such that it can serve as a kind of biological fingerprint.
Georg Dorffner (principal investigator)
Lewandowski A., Rosipal R., Dorffner G. (2012) Extracting More Information from EEG Recordings for a Better Description of Sleep. Computer Methods and Programs in Biomedicine 108(3), 961–972.
Lewandowski A., Rosipal R., Dorffner G. (2013) On the Individuality of Sleep EEG Spectra. Journal of Psychophysiology 27(3), 105–112.
Rosipal R., Lewandowski A., Dorffner G. (2013) In Search of Objective Components for Sleep Quality Indexing in Normal Sleep. Biological Psychology 94(1), 210–220.