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Perception of voices that do not exist: Tracking the temporal signatures of auditory hallucinations

Periodic Reporting for period 2 - ONOFF (Perception of voices that do not exist: Tracking the temporal signatures of auditory hallucinations)

Reporting period: 2018-03-01 to 2019-08-31

"The problem addressed in ONOFF ERC AdG project is the underlying neuronal and cognitive mechanisms for auditory hallucinations in schizophrenia, using behavioral and brain imaging methods. A subsidiary problem is how to understand the spontaneous fluctuations over time of hallucinatory episodes, and in particular what causes the ""voices"" to temporarily go away, with a long-term goal of contributing to development of new interventions, targeted on a symptom rather than on a diagnosis as such. Schizophrenia is one of the most severe mental disorders, which affects about 1% of the European population, and with enormous costs for the society. There is a changing demographic pattern of the incidence of schizophrenia which goes together with the increasing urbanization and migration into the major European cities. Thus, understanding the the most severe symptoms, auditory hallucinations, in one of the most severe mental disorders, schizophrenia is of major societal importance. The overall objectives of the project follows a model called ""Levels of explanation, which seeks to explain auditory hallucinations at different explanatory levels, from the clinical to the neuronal levels. A major issue in the ONOFF project is the fluctuations of hallucinatory episodes, and if these are related to changes in excitatory/inhibitory influences at the level of neurochemistry in the brain. Using MR spectroscopy (MRS), our group was the first to report increased levels of the excitatory neurotransmitter Glutamate. We have more recently followed-up these initial results, showing that frequency and severity of auditory hallucinations correlate positively with increased levels of glutamate in temporal brain regions, but negatively in frontal (ACC) regions, as would be predicted from the VOICE model for auditory hallucinations proposed by Hugdahl in 2009. In order to relate finding at the level of neurochemistry to findings at the level of neuroimaging, we have developed a new MR sequence to simultaneously assessing brain metabolites and functional changes seen in fMRI BOLD data. Preliminary validations show that the simultaneously acquired MRS and BOLD data is a feasible way forward. As stated in the proposal, there is a need for new approaches to cognitive training of auditory hallucinations, as well as new ways of acquiring data on frequency and content of auditory hallucinations in real-time (not only through retrospective interviews). We have for this purpose developed two smartphone apps, one for training, and another for symptom capture screening."
The achievements of the project so far can be summarized as having successfully developed a new way of simultaneous acquisition of functional MRI (fMRI) data and MR spectroscopy (MRS) data. An hypothesis put forward in the ONOFF proposal is that the spontaneous fluctuations of hallucinatory episodes over time are caused by changing influences of excitatory and inhibitory transmitter effects. Using the MRS method we have preliminary evidence of a positive correlation between Glu levels and frequency and severity of auditory hallucinations in the left upper posterior temporal lobe, and a corresponding negative correlation in the medial frontal lobe. Another achievement is that we have developed a new way of separating actively hallucinating from non-hallucinating patients while in the scanner that overcomes the limitations by using traditional methods. By comparing brain activation and metabolite action between hallucinating and non--hallucinating patients, it will be possible to identify the neurobiological parameters that characterizes an active hallucinatory episode, which in turn will give us evidence for why AH spontaneously fluctuate over time. For the BOLD fMRI part of the project we are using an Eriksen Flanker task which is a cognitive task that loads on attention and excecutive function. A third achievement is that we are currently analyzing behavioral and neuronal data from patients and controls. It is hypothesized that the up- and down-regulation of the Default Mode Network (DMN) would be aberrant in hallucinatory patients, and that this could interact with the up- and down-regulation of another, task-positive network, labelled EMN. A hypothesis is that fluctuations of AH correspond with how these networks are in or out of phase with each other, which in turn could fall down on the interaction of excitatory and inhibitory neurotransmitters. Senior researcher Sarah Weber is currently analyzing BOLD BP2 data, looking specifically at dynamic functional connectivity. This analysis may provide evidence on how AH fluctuate over time while the patients are in the scanner. PhD student Justyna Beresnewicz is working on analyzing data from white matter tracts, using DTI and tractography techniques, which would provide evidence on how functional network connectivity relate to underlying fibre structure connectivity. We have further developed a smartphone app based on the dichotic listening paradigm for cognitive training to control the voices, and one other for on-line recording of AH symptom dimensions, which will be a addition to more traditional interview procedures for getting data on AH dimensions. A final achievement is establishment of a safe data storage and analysis pipeline by setting up a project-dedicated server, and connections to UiB SAFE storage system,to handle ERC2 data.
Progress beyond the state-of-the-art is that we have moved the study of neurobiological correlates of auditory hallucinations (AH) beyond a traditional brain imaging approach by asking the question how changes at the underlying transmitter and receptor level of explanation may contribute to changes in brain activation as observed with e.g. fMRI. By adding a MR spectroscopy sequence to the traditional EPI-sequence we have been able to study how excitatory (Glutamate) and inhibitory (GABA) factors correlate with frequency and severity of AH, and are in the process to take the MRS approach one step further by setting the stage for simultaneous BOLD and MRS data acquisitions from the same brain region in real-time, using MEGA PRESS MRS sequence with insufficient water suppression. So far we have found that temporal lobe Glu concentration is positively correlated with frequency and severity of AH, while frontal lobe Glu is correspondinglynbegatively correlated. We expect to have results for the GABA transmitter as well by the end of the project period. Another progress beyond state-of-the-art is the discovery of the Extrinsic Mode Network (EMN) by Hugdahl et al. (2015) as a generalized task-positive cortical network, that is independent of the cognitive task. We have been able to show that the EMN is anti-correlated with the well-known Default Mode Network (DMN), discovered by Raichle and colleagues (2001), and that this happens when environmental demands change from rest to active processing. We will now use this new discovery to analyze data from the ONOFF project to explore if AH abrupt the EMN/DMN dynamics, and if this is related to the fluctuations of AH. A third beyond state-of-the-art progress is the continuing development and improvement of smartphone apps for cognitive training and real-time AH symptom capturing.
The MR scanner environment at the Haukeland University Hospital, Bergen, Norway
PI Kenneth Hugdahl, University of Bergen, Norway