Spontaneous brain activity observed with functional magnetic resonance imaging as a potential biomarker in neuropsychiatric disorders

Abstract

As functional magnetic resonance imaging (fMRI) studies have yielded increasing amounts of information about the brain's spontaneous activity, they have revealed fMRI's potential to locate changes in brain hemodynamics that are associated with neuropsychiatric disorders. In this paper, we review studies that support the notion that changes in brain spontaneous activity observed by fMRI can be used as potential biomarkers for diagnosis and treatment evaluation in neuropsychiatric disorders. We first review the methods used to study spontaneous activity from the perspectives of (1) the properties of local spontaneous activity, (2) the spatial pattern of spontaneous activity, and (3) the topological properties of brain networks. We also summarize the major findings associated with major neuropsychiatric disorders obtained using these methods. Then we review the pilot studies that have used spontaneous activity to discriminate patients from normal controls. Finally, we discuss current challenges and potential research directions to further elucidate the clinical use of spontaneous brain activity in neuropsychiatric disorders.

Keywords: Alzheimer’s disease; Functional connectivity; Low frequency fluctuation; Resting-state fMRI; Schizophrenia.

Fig. 1

Altered functional connectivities in the default mode network in Alzheimer’s disease. a The core brain regions in the default mode network in healthy subjects are illustrated schematically. Prominent components of this network include medial prefrontal regions, posterior regions in the medial and lateral parietal cortex, the lateral temporal cortex and the medial temporal lobe (including the hippocampus and parahippocampal gyrus). Regions within this core brain system are functionally correlated with each other and, prominently, with the hippocampal formation. The solid line represents the correlations between the core regions. b The functional connectivity between the hippocampal formation and the medial posterior regions were consistently found to be decreased or absent in patients with Alzheimer’s disease (for references, please see the main text). The dashed line represents decreased or absent correlations between the hippocampus/parahippocampal gyrus and the posterior cingulate area

Fig. 2

Altered resting-state functional connectivity in schizophrenia and Alzheimer’s disease. a Schizophrenia patients mainly showed decreased functional connectivities and such abnormalities were widely distributed throughout the entire brain rather than restricted to a few specific brain regions. b Alzheimer’s disease mainly showed decreased functional connectivities between the prefrontal and parietal lobes, but increased functional connectivities within the prefrontal lobe, parietal lobe and occipital lobe

Fig. 3

Biomarker-based predictive model for diagnosis, therapy evaluation and prognosis of neuropsychiatric disorders. Neuropsychiatric disorders are studied from three aspects: molecular, imaging and clinical. Molecular changes in the disorders are found at the DNA, RNA and protein levels and could be used as molecular biomarker for the diseases. Alterations in brain imaging characteristics are identified in structural, functional and diffusion tensor images, in which the functional image (the focus of this article) is examined from the perspectives of local spontaneous activity, functional connectivity and brain networks and can be integrated with the structural and diffusion tensor images. Altered brain imaging features could be used as brain imaging biomarkers; Clinical characteristics obtained from symptoms and neuropsychological and physiological examination of the diseases could be considered as clinical biomarkers. Taken together, the combination of the three types of biomarkers can be compared and integrated to form a predictive model for diagnosis, therapy evaluation and prognosis of the diseases and can thus provide a new standard for clinical care