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Effective connectivity between Broca's area and amygdala as a mechanism of top-down control in worry.

ABSTRACT: Individuals higher in trait worry exhibit increased activation in Broca's area during inhibitory processing tasks. To identify whether such activity represents an adaptive mechanism supporting top-down control, functional and effective connectivity of Broca's area were investigated during a task of inhibitory control. fMRI data obtained from 106 participants performing an emotion-word Stroop task were examined using psychophysiological interaction and Granger Causality (GC) analyses. Findings revealed greater directed connectivity from Broca's to amygdala in the presence of emotional distraction. Furthermore, a predictive relationship was observed between worry and the asymmetry in effective connectivity, with worriers exhibiting greater directed connectivity from Broca's to amygdala. When performing the task, worriers with greater GC directional asymmetry were more accurate than worriers with less asymmetry. Present findings indicate that individuals with elevated trait worry employ a mechanism of top-down control in which communication from Broca's to amygdala fosters successful compensation for interference effects.

SUBMITTER: Guha A

PROVIDER: S-EPMC7517719 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Effective connectivity between Broca's area and amygdala as a mechanism of top-down control in worry.

Guha Anika A Spielberg Jeffrey J Lake Jessica J Popov Tzvetan T Heller Wendy W Yee Cindy M CM Miller Gregory A GA

Clinical psychological science : a journal of the Association for Psychological Science 20191024 1

Individuals higher in trait worry exhibit increased activation in Broca's area during inhibitory processing tasks. To identify whether such activity represents an adaptive mechanism supporting top-down control, functional and effective connectivity of Broca's area were investigated during a task of inhibitory control. fMRI data obtained from 106 participants performing an emotion-word Stroop task were examined using psychophysiological interaction and Granger Causality (GC) analyses. Findings re ...[more]

PMID: 32983628

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Project description:ObjectiveWe hypothesized that compared to healthy controls, long-term abstinent substance dependent individuals (SDI) will differ in their effective connectivity between large-scale brain networks and demonstrate increased directional information from executive control to interoception-, reward-, and habit-related networks. In addition, using graph theory to compare network efficiencies we predicted decreased small-worldness in SDI compared to controls.Methods50 SDI and 50 controls of similar sex and age completed psychological surveys and resting state fMRI. fMRI results were analyzed using group independent component analysis; 14 networks-of-interest (NOI) were selected using template matching to a canonical set of resting state networks. The number, direction, and strength of connections between NOI were analyzed with Granger Causality. Within-group thresholds were p<0.005 using a bootstrap permutation. Between group thresholds were p<0.05, FDR-corrected for multiple comparisons. NOI were correlated with behavioral measures, and group-level graph theory measures were compared.ResultsCompared to controls, SDI showed significantly greater Granger causal connectivity from right executive control network (RECN) to dorsal default mode network (dDMN) and from dDMN to basal ganglia network (BGN). RECN was negatively correlated with impulsivity, behavioral approach, and negative affect; dDMN was positively correlated with impulsivity. Among the 14 NOI, SDI showed greater bidirectional connectivity; controls showed more unidirectional connectivity. SDI demonstrated greater global efficiency and lower local efficiency.ConclusionsIncreased effective connectivity in long-term abstinent drug users may reflect improved cognitive control over habit and reward processes. Higher global and lower local efficiency across all networks in SDI compared to controls may reflect connectivity changes associated with drug dependence or remission and requires future, longitudinal studies to confirm.

Project description:Visual hallucinations are common in Parkinson's disease and are associated with a poorer quality of life and a higher risk of dementia. An important and influential model that is widely accepted as an explanation for the mechanism of visual hallucinations in Parkinson's disease and other Lewy body diseases is that these arise due to aberrant hierarchical processing, with impaired bottom-up integration of sensory information and overweighting of top-down perceptual priors within the visual system. This hypothesis has been driven by behavioural data and supported indirectly by observations derived from regional activation and correlational measures using neuroimaging. However, until now, there was no evidence from neuroimaging for differences in causal influences between brain regions measured in patients with Parkinson's hallucinations. This is in part because previous resting-state studies focused on functional connectivity, which is inherently undirected in nature and cannot test hypotheses about the directionality of connectivity. Spectral dynamic causal modelling is a Bayesian framework that allows the inference of effective connectivity-defined as the directed (causal) influence that one region exerts on another region-from resting-state functional MRI data. In the current study, we utilize spectral dynamic causal modelling to estimate effective connectivity within the resting-state visual network in our cohort of 15 Parkinson's disease visual hallucinators and 75 Parkinson's disease non-visual hallucinators. We find that visual hallucinators display decreased bottom-up effective connectivity from the lateral geniculate nucleus to primary visual cortex and increased top-down effective connectivity from the left prefrontal cortex to primary visual cortex and the medial thalamus, as compared with non-visual hallucinators. Importantly, we find that the pattern of effective connectivity is predictive of the presence of visual hallucinations and associated with their severity within the hallucinating group. This is the first study to provide evidence, using resting-state effective connectivity, to support a model of aberrant hierarchical predictive processing as the mechanism for visual hallucinations in Parkinson's disease.

Dataset Information

Effective connectivity between Broca's area and amygdala as a mechanism of top-down control in worry.

Publications

Effective connectivity between Broca's area and amygdala as a mechanism of top-down control in worry.

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