Circuit to construct mapping: a mathematical tool for assisting the diagnosis and treatment in major depressive disorder

被引:12
作者
Bielczyk, Natalia Z. [1 ,2 ]
Buitelaar, Jan K. [1 ,2 ]
Glennon, Jeffrey C. [1 ,2 ]
Tiesinga, Paul H. E. [1 ,3 ]
机构
[1] Donders Inst Brain Cognit & Behav, Nijmegen, Netherlands
[2] Radboud Univ Nijmegen, Med Ctr, Dept Cognit Neurosci, NL-6525 GA Nijmegen, Netherlands
[3] Radboud Univ Nijmegen, Dept Neuroinformat, NL-6525 GA Nijmegen, Netherlands
关键词
major depressive disorder; modeling; circuit; diagnosis; research domain criteria project; dynamical systems; BRAIN FUNCTIONAL NETWORKS; DEFAULT MODE NETWORK; EFFECTIVE CONNECTIVITY; PRINCIPAL COMPONENTS; RESTING BRAIN; FMRI; ANTIDEPRESSANT; CLASSIFICATION; STIMULATION; DOPAMINE;
D O I
10.3389/fpsyt.2015.00029
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
Major depressive disorder (MDD) is a serious condition with a lifetime prevalence exceeding 16% worldwide. MDD is a heterogeneous disorder that involves multiple behavioral symptoms on the one hand and multiple neuronal circuits on the other hand. In this review, we integrate the literature on cognitive and physiological biomarkers of MDD with the insights derived from mathematical models of brain networks, especially models that can be used for fMRI datasets. We refer to the recent NIH research domain criteria initiative, in which a concept of "constructs" as functional units of mental disorders is introduced. Constructs are biomarkers present at multiple levels of brain functioning cognition, genetics, brain anatomy, and neurophysiology. In this review, we propose a new approach which we called circuit to construct mapping (CCM), which aims to characterize causal relations between the underlying network dynamics (as the cause) and the constructs referring to the clinical symptoms of MDD (as the effect). CCM involves extracting diagnostic categories from behavioral data, linking circuits that are causal to these categories with use of clinical neuroimaging data, and modeling the dynamics of the emerging circuits with attractor dynamics in order to provide new, neuroimaging-related biomarkers for MDD. The CCM approach optimizes the clinical diagnosis and patient stratification. It also addresses the recent demand for linking circuits to behavior, and provides a new insight into clinical treatment by investigating the dynamics of neuronal circuits underneath cognitive dimensions of MDD. CCM can serve as a new regime toward personalized medicine, assisting the diagnosis and treatment of MDD.
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页数:15
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