Daniel Lundqvist

While psychotic disorders such as schizophrenia represent a significant clinical burden for the individual and large costs for the society, not much is known about the underlying causes. The effort to explain psychotic disorders must include an information processing level since subjective experiences and thoughts are fundamentally altered. We have suggested that there is an unstable low-level information processing in psychosis. In order to compensate for such noise, overly strong top-down influence from prefrontal circuits are recruited and may cause psychotic symptoms like delusions. In the present project we test our hypotheses using a multi-imaging approach. We will perform dynamic network analyses, i.e. connectomics, in MRI-datasets on psychosis patients, and associated phenotypes, with a focus on alterations in prefrontal circuits. We will relate our results to longitudinal behavioral outcomes and treatment effects as well as genetic risk and synaptic density (measured with PET). The results will probe whether these measurements can be used in future precision medicine for clinical assessment of patients. We will also perform task-based functional imaging studies (fMRI and MEG) of psychosis patients to study belief formation dependent on prefrontal cortex, and test causality of these circuits with brain stimulation in non-patients. The project also supports core costs of several ongoing clinical projects such as Karolinska Schizophrenia Project (KaSP).

Background: The age standardised rate of yearly new cancer cases is 190/100 000 globally, by WHO. 30-40% of these will develop depression. There is currently no specific antidepressant treatment regime implemented in the cancer population. This is in spite of the specific needs given by concurrent cancer treatments, limited quality of life from the cancer per se and the often limited life expectancy from a cancer disease. A single dose of psilocybin combined with 3 hours of psychological support has shown rapid (within days) and long term (months or years) antidepressant effect in several small studies in different cancer populations. Large, well designed RCTs are still lacking, as is response predictors for treatment guidance. I am PI of the first RCT of psilocybin treament of depression in Sweden, expected to end randomisation in june 2022. CAPSI: 100 patients with cancer and depression will be randomised to psilocybin or active placebo (2:1) at 4 different regions in Sweden during 2024-2025. Primary end point is depressive symptoms 6 weeks post dose and follw up is 6 months. All subjects will undergo EEG and blood sampling, a subsample (n=50) will also undergo MEG and fMRI, and 25 of them also PET, in order to develop a EEG proxy response signature. Together with markers in blood we will develop a predictor model for psilocybin treatment response. All data will be used to motivate a phase three study with the same PICO and further development of the response markers.

Purpose and goal: Through the program for a digital Europe (DIGITAL), the European Commission wants to increase the efficiency, resilience and sustainability of the EU´s healthcare system, and reduce inequalities in healthcare within the EU. AI and robotics are considered critical areas that need to be developed to reach this objective. TEF HEALTH call is part of the European Strategy for Artificial Intelligence (AI) which aims to optimize the development of AI and promote trust in and use of AI-based software and hardware solutions. Expected results and effects: By making available and combining unique infrastructures for exhaustive in vivo imaging, multimodal ex vivo profiling, and safe and AI-based combinations of these, the Swedish node (CIR, SciLifeLab and RISE) offers internationally competitive opportunities to help European SMEs identify, develop, support and accelerate new and improved precision health applications based on AI-based hardware and software solutions. TEF-Health-konsortiet is expected to serve 500 TEF users by the end of the project and test a total of 5,000 solutions. Approach and implementation: TEF-health begins January 2023. Within the Swedish node, we will organize and make available: IN-VIVO imaging and EX-VIVO OMICS infrastructure, includaing platform access & expert support. A full-service AI development platform, a DATA HUB including retrospectively collected data, a PRECISION DATA HUB including prospectively collected data, and an AI BUSINESS development lab. Sweden contributes to all WPs, and leads WP9 Use cases and demonstrators, where we make Societal challenges, TEF applications, and SME solutions inventories

Use cases database and Demonstrator cases

We will develop an improved and more accessible HD-MEG functional neuroimaging system. By the end of this project, we aim to demonstrate a doubling in spatial resolution as well as a biomarker for cardiovascular disease and improved epilepsy outcomes. The work unites ongoing R&D with advanced neuroimaging technology

it is boosted by the infrastructures available at GU, SUH--including a new and dedicated research lab--Chalmers, and KI combined with our growing group of students and international collaborators. We advance new theories, next-generation hardwares, and innovative analysis routines for challenging the state-of-the-art in neuroimaging.Validation of our technical capabilities are kick-started with ongoing benchmarking studies as well as cardiovascular disease and epilepsy investigations. By bridging technical development with our growing toolkit of clinically validated protocols, solutions to healthcare problems associated with the brain can reach patients sooner. Such medical-technical collaboration also brings both areas to new levels of understanding.The integration of theory, hardware, and software enables the ultimate in sensitivity to neural activity, approaching the limits of what can be safely and non-invasively extracted from the human brain. We are a collaborative team of physicists, engineers, neuroscientists, clinical neurophysiologists, and psychiatrists that are ready and motivated to develop the technology and validate our approach.

Magnetoencephalography (MEG) is a non-invasive, passive and completely silent method that directly measures the magnetic fields generated by ongoing neuronal brain activity. With MEG, brain activity patterns can be resolved at an unrivalled temporal and spatial resolution.Next-generation MEG sensors, so-called on-scalp MEG sensors, register even more of the brain’s activity, at even better detail, detecting clinically relevant activity unseen by conventional MEG.The advancement of on-scalp MEG is thus of very high relevance for the fields of neuroscience and neurology and holds a strong promise to improve the usefulness of MEG in, for example, evaluation and presurgical planning of epilepsy patients.Sweden has made important contributions to advancing on-scalp MEG sensor development, academic and clinical applications, and method development. Continued advancement in this field now requires the support from a national on-scalp MEG platform, at which at which beyond state-of-the-art demonstrations and the continued development of academic and clinical applications can be performed.The on-scalp MEG field is now at a critical window of opportunity, wherein Sweden’s unique momentum can be strategically strengthened and accelerated. On-scalp MEG sensors are now commercially available, but very few labs with whole-head sensor coverage yet exist.With this application, we aim to integrate an internationally competitive 128 channel on-scalp MEG system into the well-functioning national MEG lab NatMEG. The on-scalp MEG technology is now mature enough for this leap.The proposed on-scalp MEG system can be directly integrated into the current national MEG lab system and operations, and thereby demonstrate the advantages of different MEG sensor technologies, and provide a platform for educating new generations of on-scalp MEG users.