This Research Topic is part of the article collection series,
Mapping psychopathology with fMRI and effective connectivity analysisIt is of no doubt that we took the dysconnection view more seriously with the advent of connectivity analysis in vivo. There is a growing appreciation that many psychiatric (and neurological) conditions can be understood as functional disconnection syndromes – as reflected in aberrant functional integration and synaptic connectivity. This Research Topic is part of the “Mapping psychopathology with fMRI and effective connectivity analysis” series and considers recent advances in understanding psychopathology in terms of aberrant connectivity – as measured noninvasively using functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). For example, major depressive disorder (MDD) is a common psychiatric disorder that is characterized by persistent feelings of negative moods, low self-esteem, and a loss of interest or pleasure in formerly pleasurable activities. Convergent findings from neuroimaging studies suggest that MDD is associated with dysregulation of specific brain networks, rather than a dysfunction of single brain regions. Functional connectivity – defined as statistical dependency among regional time series – has been widely used to identify candidate networks implicated in MDD. These networks include the default mode network, the executive control network, the affective network, etc. However, because functional connectivity does not support inferences about directed (causal) brain connections, the changes in information flow in these distributed systems remain largely unknown. Additionally, structural connectivity enables us to understand the pathophysiology of this disorder from the perspective of disrupted white structural matter. Likewise, the structural connectivity is not directional.
Recently, there has been increasing interest in inferring directed connectivity (effective connectivity) from fMRI data. Effective connectivity refers to the influence that one neural system exerts over another and quantifies the directed coupling among brain regions – and how they change with pathophysiology. Compared to functional connectivity, effective connectivity allows one to understand how brain regions interact with each other in terms of context-sensitive changes and directed coupling – and therefore may provide mechanistic insights into the neural basis of psychopathology. Additionally, structural connectivity enable us to understand the pathophysiology of disease from the perspective of disrupted white matter.
This Research Topic aims to continue investigating the neural circuitry of major neuropsychiatric disorders (e.g., MDD, bipolar disorder, schizophrenia, Alzheimer's, Huntington's and Parkinson’s disease, etc.) using fMRI. In addition, this Research Topic focuses on the effects of treatment, including psychotropic drugs and neuromodulation, on directed coupling among brain regions – and whether alterations in connectivity persist in remitted subjects. Furthermore, we hope to address the relationship between persistent changes in connectivity and relapse.
We welcome both original research articles and other types of manuscripts. General methods could be used to construct functional and structural connectivity. Established models of effective connectivity include psychophysiological interaction (PPI), structural equation modelling (SEM), and dynamic causal modelling (DCM). DCM is unique because it explicitly models the interaction among brain regions in terms of latent neuronal activity. Moreover, recent advances in DCM such as stochastic and spectral DCM, make it possible to characterize the interaction between different brain regions both at rest and during a cognitive task. New findings by DCM demonstrate symptom-specific excitatory and inhibitory afferents in patients, providing insights into the neural mechanisms underlying psychopathology.