Search bioRxiv⌕ Search

bioRxiv · 10.1101/573634

A failed top-down control from prefrontal cortex to amygdala in generalized anxiety disorder: evidence from resting-state fMRI with Granger causality analysis

Abstract

ObjectiveIn generalized anxiety disorder (GAD), abnormal top-down control from prefrontal cortex (PFC) to amygdala is a widely accepted hypothesis through which \"emotional dysregulation model\" may be explained. However, whether and how the PFC directly exerted abnormal top-down control on amygdala remained largely unknown. We aim to investigate the amygdala-based effective connectivity by using Granger causality analysis (GCA).\n\nMethodsThirty-five drug-naive patients with GAD and thirty-six healthy controls (HC) underwent resting-state functional MR imaging. We used seed-based Granger causality analysis to examine the effective connectivity between the bilateral amygdala and the whole brain. The amygdala-based effective connectivity was compared between the two groups.\n\nResultsIn HC, the left middle frontal gyrus exerted inhibitory influence on the right amygdala, while in GAD group, this influence was disrupted (single voxel P < 0.001, Gaussian random field corrected with P < 0.01).\n\nConclusionOur finding might provide new insight into the \"insufficient top-down control\" hypothesis in GAD.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Dong, M., Xia, L., Lu, M., Li, C., Xu, K., Zhang, L.. 2019-03-12. A failed top-down control from prefrontal cortex to amygdala in generalized anxiety disorder: evidence from resting-state fMRI with Granger causality analysis. https://doi.org/10.1101/573634

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

E2F4 gene therapy reverses established synaptic and cognitive deficits and remodels learning-associated signaling in Alzheimer's disease mice

Alzheimer's disease (AD) causes progressive synaptic dysfunction, neurodegeneration, and cognitive decline, yet strategies capable of reversing established deficits remain limited. Here, we show that neuronal expression of a p38MAPK phosphorylation-resistant human E2F4 variant (hE2F4DN), delivered by adeno-associated virus, restores hippocampal long-term potentiation and memory in homozygous 5xFAD mice after functional impairment is established. Treatment also reduces amyloid-{beta} and phospho-tau pathology and prevents hippocampal neuronal loss. Integrated proteomic and phosphoproteomic analyses reveal remodeling of metabolic, redox, neuroimmune, synaptic-vesicle, and GSK3{beta}-associated signaling pathways. Following contextual fear conditioning, hE2F4DN-treated mice exhibit broader learning-associated synaptic proteomic signatures and distinct phosphoregulatory responses involving synaptic machinery. These findings demonstrate that E2F4 gene therapy can reverse established synaptic and cognitive deficits while preserving neuronal integrity and reshaping molecular responses to learning, identifying E2F4 phosphorylation as a potential therapeutic target for advanced AD states.

neuroscience↗

Complex Spatial and Temporal Organization of Functional Brain Networks

Recent research exploring brain-behavior associations has relied on the language of complex systems to understand how stable behavioral individual differences emerge from brain function. At the same time, advances in neuroimaging have provided greater insight into both the topological and temporal properties of macroscale cortical networks. These new approaches offer a potential avenue for understanding how functional activity in the brain might behave in a manner that aligns with complex-systems interpretations of psychological traits. The present study used resting-state data from the Human Connectome project (N = 994) to explore associations between the spatial and temporal features of functional brain networks. Using an adaptive frequency approach to explore brain function at different timescales together with a family of methods from complex systems theory, we identified patterns of brain state organization reflecting a state-trait continuum, with more stable trait-like dynamics and greater functional coupling between networks in lower frequency oscillations. Additionally, we found evidence of greater coupling across timescales in brain networks associated with higher-order cognition. This research supports interpretations of brain organization as a spatiotemporal hierarchy and provides future avenues for exploring brain-behavior associations from a complex system perspective.

neuroscience↗

A Mechanistic Account of Dedifferentiation in the Aging Visual System

To uncover the mechanisms of age-related dedifferentiation, we simulated neural degradation in a computational model of the ventral visual stream. Severing connections or adding noise, whether in inferotemporal cortex (IT) or upstream, reduced IT differentiation, indicating that dedifferentiation need not originate locally. Degrading peripheral V1, which preferentially drove place-selective IT neurons, selectively reduced place differentiation, a candidate mechanism for the stronger place dedifferentiation reported in aging.

neuroscience↗