Differential modulation of the default mode network via serotonin-1A receptors

Department of Psychiatry and Psychotherapy, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, 1090 Vienna, Austria.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 02/2012; 109(7):2619-24. DOI: 10.1073/pnas.1117104109
Source: PubMed


Reflecting one's mental self is a fundamental process for evaluating the personal relevance of life events and for moral decision making and future envisioning. Although the corresponding network has been receiving growing attention, the driving neurochemical mechanisms of the default mode network (DMN) remain unknown. Here we combined positron emission tomography and functional magnetic resonance imaging to investigate modulations of the DMN via serotonin-1A receptors (5-HT(1A)), separated for 5-HT autoinhibition (dorsal raphe nucleus) and local inhibition (heteroreceptors in projection areas). Using two independent approaches, regional 5-HT(1A) binding consistently predicted DMN activity in the retrosplenial cortex for resting-state functional magnetic resonance imaging and the Tower of London task. On the other hand, both local and autoinhibitory 5-HT(1A) binding inversely modulated the posterior cingulate cortex, the strongest hub in the resting human brain. In the frontal part of the DMN, a negative association was found between the dorsal medial prefrontal cortex and local 5-HT(1A) inhibition. Our results indicate a modulation of key areas involved in self-referential processing by serotonergic neurotransmission, whereas variations in 5-HT(1A) binding explained a considerable amount of the individual variability in the DMN. Moreover, the brain regions associated with distinct introspective functions seem to be specifically regulated by the different 5-HT(1A) binding sites. Together with previously reported modulations of dopamine and GABA, this regional specialization suggests complex interactions of several neurotransmitters driving the default mode network.

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