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Neural Network Bases of Healthy and Aberrant Belief Updating

Subject Area Biological Psychology and Cognitive Neuroscience
Human Cognitive and Systems Neuroscience
Personality Psychology, Clinical and Medical Psychology, Methodology
Term since 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 461947532
 
Background: Dynamic belief updating is key for healthy cognition and seems to be impaired in schizophrenia. Recent advances have yielded new insights into the large-scale brain circuit operations underlying dynamic belief updating. The active reset of belief updating computations in specialized networks of the cerebral cortex, triggered by the transient (phasic) activation of brainstem arousal systems, may play a key role in this process. Clinical research has discovered aberrations of baseline arousal levels in schizophrenia. We propose that aberrations of baseline arousal reduce phasic arousal responses during belief updating; this impairs the large-scale cortical network resets required for updating the belief state following environmental changes. We plan to unravel this putative mechanistic cascade in the healthy human brain and quantify its aberrations in schizophrenia. Aims & hypotheses: We aim to (i) identify large-scale signatures and decipher the functional role of cortical network resets following change points; (ii) unravel the dependence of task-evoked, phasic arousal responses, following change points, on baseline arousal levels; and (iii) quantify aberrations of phasic arousal and cortical network reset in schizophrenia. Based on pilot results, we expect that change point-triggered cortical network resets will manifest in distinct modulations of neural variability in evidence-encoding versus belief-encoding cortical areas. This will facilitate the substitution of an old by a new belief state. We further expect that healthy individuals with higher baseline arousal will exhibit reduced change point-triggered phasic arousal responses, which will translate into less effective network resets and less flexible belief updating. Finally, we expect that such baseline arousal-dependent impairments of the belief-updating cascade may be amplified in schizophrenia. Methods: We plan to test these hypotheses with an integrated application of behavioral modeling, arousal tracking in daily life through experience sampling, laboratory assessment of arousal through pupillometry and ECG, and magnetoencelphalographic (MEG) assessment of large-scale cortical network dynamics. Novel analysis techniques will enable us to interrogate the large-scale circuit operations underlying belief updating in the human brain with high spatial and temporal specificity. To build a solid foundation for our conclusions, we will assess network reset signatures in multiple existing pupillometry-MEG data sets from the healthy brain. In a new data set, we will compare arousal and cortical belief updating dynamics between schizophrenia patients and healthy controls. Impact: This project will advance the fundamental understanding of healthy and aberrant belief updating and may pave the way for a biomarker assay of the interplay of brainstem arousal systems and cortical computation in schizophrenia.
DFG Programme Research Units
 
 

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