Funding & Rewards

Mood disorders affect up to fifteen percent of the population, any given year. Today’s treatment options are plagued with low response and high relapse rates, and can be time and resource intensive. Further, up to one third of patients suffering from major depression do not respond to standard treatments. New treatment options that alter the brains level of neuroplasticity (its ability to adapt to change and reconfigure itself) show promising results, but either show transient effects or require multiple and/or maintenance treatments. Here we wish to combine two methods that induce neuroplasticity, intravenous sub-anesthetic ketamine infusion and transcranial magnetic stimulation (TMS), in a one day protocol for treatment of depression. The planned clinical RCT will involve one treatment of ketamine, followed by two sessions of ‘theta-burst stimulation’ (TBS; an approved therapeutic TMS protocol), controlled by an active placebo group (sub-anesthetic midazolam infusion) and sham-TMS. The hypothesis is that one method (TMS) can strengthen the effect of the other (ketamine) such that the anti-depressant effect is stronger and/or lasts longer. A positive result may reduce the need for multiple treatments or increase the time interval between treatments.

In the terminal stage before death, patients often become partially or completely unresponsive and unable to communicate coherently with caretakers. Although unresponsiveness is often associated with unconsciousness, recent research has shown that a surprisingly high proportion of unresponsive patients retain consciousness in some patient populations (e.g. as much as 43% of unresponsive patients suffering from disorders of consciousness have been shown to be misclassified as unconscious). This may also be true for dying patients, meaning that they may suffer from symptoms such as pain, thirst, and anxiety, that are not recognized and treated. However, this potential issue has been largely ignored, and would benefit from being addressed using state-of-the art methods. Our cross-disciplinary team of experts on brain-based measures of consciousness, clinical palliative care, and medical ethics aims to contribute to solving this issue. Specifically, we will assess how the best brain-based measures of consciousness can be used in palliative care, to understand when and how often unresponsive dying patients retain consciousness covertly. In phase 1 of our project, we will select, adapt, and test theoretically and empirically sound candidate measures that are likely to be useful for detecting consciousness in unresponsive patients. These measures will be evaluated for use in the palliative care settings in control experiments with healthy volunteers and patients. In phase 2, we will apply the most promising candidate measures in unresponsive, dying patients, and evaluate their clinical value and apparent capacity to detect covert consciousness. Importantly, the project will be conducted in close collaboration with patients, their next of kin, interest organizations, and clinical staff, to ensure our tools can be used in ways that improve care for the dying and maintain dignity in a difficult time, rather than just adding to the interventional load at the end of life.

We won a grant to organize an open symposium on scientific theories of consciousness, specifically focused on the integrated in formation theory. Speakers; Johan F. Storm, Jeremia Hendren, Matteo Grasso, and Bjørn E Juel

I won the award for best poster at the national neuroscience conference for PhDs at Sommarøy near Tromsø. It granted me both a cash prize and attendance with the poster to the European neuroscience neuroscience conference (FENS) the following year.

This project aimed to acquire theoretical and computational tools for analyzing causal interactions in complex networks within the framework of Integrated Information Theory (IIT). The work was carried out during a research visit to the laboratory of Giulio Tononi, under the primary supervision of Larissa Albantakis, one of the main developers of IIT’s mathematical formalism. The project focused on learning to apply IIT’s causal analysis framework to evolving artificial agents (“animats”) with Boolean network nervous systems, evolved via genetic algorithms in simulated environments. By applying IIT-inspired causal analysis to evolving artificial agents, the project examined the extent to which an agent’s actions are driven by internal network dynamics versus external sensory inputs. Using adaptive agents equipped with small Markov Brains, evolved under varying sensor capacities and task demands, the work quantified the actual causes of actions and traced their causal histories over time. The results showed that the degree to which behavior was internally caused—rather than environmentally driven—systematically depended on task difficulty and sensor constraints, highlighting how intrinsic causal structure adapts to environmental demands. These findings formed the basis of a peer-reviewed conference paper and an oral presentation at the Artificial Life (ALIFE) conference, and provided a concrete demonstration of how causal analysis frameworks developed in IIT can be used to study autonomy, agency, and internal control in complex adaptive systems.