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Koirala, N.

Publications and source records attributed to Koirala, N..

2 recordsLinked to original sources

Community driven dynamics of oscillatory network responses to threat

Physiological responses to threat stimuli involve neural synchronized oscillations in cerebral networks with distinct organization properties. Community architecture within these networks and its dynamic adaptation could play a critical role in achieving optimal physiological responses.\n\nHere we applied dynamic network analyses to address the early phases of threat processing at the millisecond level, describing multi-frequency (theta and alpha) integration and basic reorganization properties (flexibility and clustering) that drive physiological responses. We quantified cortical and subcortical network interactions and captured illustrative reconfigurations using community allegiance as essential fingerprints of large-scale adaptation.\n\nA theta band driven community reorganization of key anatomical regions forming the threat network (TN) along with transitions of nodes from the dorsal attention (DAN) and salience (SN) circuits predict the optimal physiological response to threat. We show that increase flexibility of the community network architecture drives the physiological responses during instructed threat processing. Nodal switches modulate the directionality of information flows in the involved circuits.\n\nThese results provide a captivating perspective of flexible network responses to threat and shed new light on basic physiological principles relevant for the development of stress- and threat-related mental disorders.

neuroscience

Cortical network fingerprints predict deep brain stimulation outcome in dystonia

BackgroundDeep brain stimulation (DBS) is an effective evidence-based therapy for dystonia. However, no unequivocal predictors of therapy responses exist. We investigate whether patients optimally responding to DBS present distinct brain network organization and structural patterns.\n\nMethodsBased on a German multicentre cohort of eighty-two dystonia patients with segmental and generalized dystonia, who received DBS implantation in the globus pallidus internus patients were classified based on the clinical response 36 months after DBS, as superior-outcome group or moderate-outcome group, as above or below 70% motor improvement, respectively. Fifty-one patients met MRI-quality and treatment response requirements (mean age 51.3 {+/-} 13.2 years; 25 female) and were included into further analysis. From preoperative MRI we assessed cortical thickness and structural covariance, which were then fed into network analysis using graph theory. We designed a support vector machine to classify subjects for the clinical response based on group network properties and individual grey matter fingerprints.\n\nResultsThe moderate-outcome group showed cortical atrophy mainly in the sensorimotor and visuomotor areas and disturbed network topology in these regions. From all the structural integrity of the cortical mantle explained about 45% of the stimulation amplitude. Classification analyses achieved 88% of accuracy using individual grey matter atrophy patterns to predict DBS outcome.\n\nConclusionsThe analysis of cortical integrity and network properties could be developed into independent predictors to identify dystonia patients who benefit from DBS.

neuroscience