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Pyatigorskaya, N.

Publications and source records attributed to Pyatigorskaya, N..

2 recordsLinked to original sources
bioRxiv2024

The role of dopaminergic, cholinergic and noradrenergic networks in hyposmia in Parkinson's disease

BackgroundOlfactory impairment is frequently observed in Parkinsons disease (PD) before motor symptom onset. Patients with isolated rapid eye movement sleep behaviour disorder (iRBD) are at risk to develop PD and present olfactory dysfunction. Subcortical neuromodulatory nuclei including the substantia nigra, the nucleus basalis of Meynert, and the locus coeruleus, may all contribute to olfactory dysfunction. ObjectiveThe objective of this study was to understand the network alterations underlying olfactory dysfunction in PD and in the early prodromal iRBD patients using multimodal MRI. MethodsPD (n = 107), iRBD patients (n = 35) and healthy controls (HC, n = 39) were recruited from the ICEBERG cohort for a cross-sectional study. We separated subjects in Healthy Controls, iRBD patients, and PD patients with or without RBD and with or without anosmia. Olfactory, motor, and cognitive scores were assessed and combined with multimodal imaging. ResultsWe found that olfaction positively correlated with (i) striatal DaT signal in PD patients; (ii) neuromelanin contrast in the locus coeruleus and (iii) Nucleus Basalis of Meynert grey matter (GM) volume in all patients. These signals were uncorrelated with motor and cognitive scores. Functional connectivity was reduced in regions of the cholinergic olfactory network in anosmic patients. Functional connectivity was also reduced in the noradrenergic network of patients with RBD. DiscussionOur results indicate the implication of the cholinergic network in PD patients with anosmia and a contribution of the noradrenergic network to olfactory dysfunction, only in patients with RBD.

neuroscience↗
bioRxiv2021

Unifying turbulent dynamics framework distinguishes different brain states

Recently, significant advances have been made by identifying the levels of synchronicity of the underlying dynamics of a given brain state. This research has demonstrated that unconscious dynamics tend to be more synchronous than those found in conscious states, which are more asynchronous. Here we go beyond this dichotomy to demonstrate that the different brain states are always underpinned by spatiotemporal chaos but with dissociable turbulent dynamics. We investigated human neuroimaging data from different brain states (resting state, meditation, deep sleep, and disorders of consciousness after coma) and were able to distinguish between them using complementary model-free and model-based measures of turbulent information transmission. Our model-free approach used recent advances describing a measure of information cascade across spatial scales using tools from turbulence theory. Complementarily, our model-based approach used exhaustive in silico perturbations of whole-brain models fitted to the empirical neuroimaging data, which allowed us to study the information encoding capabilities of the brain states. Overall, the current framework demonstrates that different levels of turbulent dynamics are fundamental for describing and differentiating between brain states.

neuroscience↗