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      Network-Dependent Modulation of COMT and DRD2 Polymorphisms in Healthy Young Adults

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          Abstract

          Nonlinear modulation of the dopamine signaling on brain functions can be estimated by the interaction effects of dopamine-related genetic variations. We aimed to explore the interaction effects of COMT rs4680 and DRD2 rs1076560 on intra-network connectivity using independent component analysis. In 250 young healthy adults, we identified 11 meaningful resting-state networks (RSNs), including the salience, visual, auditory, default-mode, sensorimotor, attention and frontoparietal networks. A two-way analysis of covariance was used to investigate COMT×DRD2 interactions on intra-network connectivity in each network, controlling for age, gender and education. Significant COMT×DRD2 interaction was found in intra-network connectivity in the left medial prefrontal cortex of the anterior default-mode network, in the right dorsolateral frontal cortex of the right dorsal attention network, and in the left dorsal anterior cingulate cortex of the salience network. Post hoc tests revealed that these interactions were driven by the differential effects of DRD2 genotypes on intra-network connectivity in different COMT genotypic subgroups. Moreover, even in the same COMT subgroup, the modulation effects of DRD2 on intra-network connectivity were different across RSNs. These findings suggest a network-dependent modulation of the DA-related genetic variations on intra-network connectivity.

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          Electrophysiological signatures of resting state networks in the human brain.

          Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1-80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.
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            Getting formal with dopamine and reward.

            Recent neurophysiological studies reveal that neurons in certain brain structures carry specific signals about past and future rewards. Dopamine neurons display a short-latency, phasic reward signal indicating the difference between actual and predicted rewards. The signal is useful for enhancing neuronal processing and learning behavioral reactions. It is distinctly different from dopamine's tonic enabling of numerous behavioral processes. Neurons in the striatum, frontal cortex, and amygdala also process reward information but provide more differentiated information for identifying and anticipating rewards and organizing goal-directed behavior. The different reward signals have complementary functions, and the optimal use of rewards in voluntary behavior would benefit from interactions between the signals. Addictive psychostimulant drugs may exert their action by amplifying the dopamine reward signal.
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              The principal features and mechanisms of dopamine modulation in the prefrontal cortex.

              Mesocortical [corrected] dopamine (DA) inputs to the prefrontal cortex (PFC) play a critical role in normal cognitive process and neuropsychiatic pathologies. This DA input regulates aspects of working memory function, planning and attention, and its dysfunctions may underlie positive and negative symptoms and cognitive deficits associated with schizophrenia. Despite intense research, there is still a lack of clear understanding of the basic principles of actions of DA in the PFC. In recent years, there has been considerable efforts by many groups to understand the cellular mechanisms of DA modulation of PFC neurons. However, the results of these efforts often lead to contradictions and controversies. One principal feature of DA that is agreed by most researchers is that DA is a neuromodulator and is clearly not an excitatory or inhibitory neurotransmitter. The present article aims to identify certain principles of DA mechanisms by drawing on published, as well as unpublished data from PFC and other CNS sites to shed light on aspects of DA neuromodulation and address some of the existing controversies. Eighteen key features about DA modulation have been identified. These points directly impact on the end result of DA neuromodulation, and in some cases explain why DA does not yield identical effects under all experimental conditions. It will become apparent that DA's actions in PFC are subtle and depend on a variety of factors that can no longer be ignored. Some of these key factors include distinct bell-shaped dose-response profiles of postsynaptic DA effects, different postsynaptic responses that are contingent on the duration of DA receptor stimulation, prolonged duration effects, bidirectional effects following activation of D1 and D2 classes of receptors and membrane potential state and history dependence of subsequent DA actions. It is hoped that these factors will be borne in mind in future research and as a result a more consistent picture of DA neuromodulation in the PFC will emerge. Based on these factors, a theory is proposed for DA's action in PFC. This theory suggests that DA acts to expand or contract the breadth of information held in working memory buffers in PFC networks.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                08 December 2015
                2015
                : 5
                : 17996
                Affiliations
                [1 ]Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital , Tianjin 300052, China
                [2 ]School of Medical Imaging, Tianjin Medical University , Tianjin, China
                Author notes
                Article
                srep17996
                10.1038/srep17996
                4672286
                26642826
                7fbbddc4-de3c-4411-b310-335c2e7012c8
                Copyright © 2015, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 28 May 2015
                : 07 September 2015
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