Some previous evidence suggests that postural related syncope is associated with defective mechanisms of cerebrovascular (CB) and cardiovascular (CV) control. We characterized the information processing in short-term CB regulation, from the variability of mean cerebral blood flow velocity (CBFV) and mean arterial pressure (AP), and in CV regulation, from the variability of heart period (HP) and systolic AP (SAP), in ten young subjects developing orthostatic syncope in response to prolonged head-up tilt testing. We exploited a novel information-theoretic approach that decomposes the information associated with a variability series into three amounts: the information stored in the series, the information transferred to the series from another series, and the information unexplained by the knowledge of both series. With this approach we were able to show that, compared with the first minutes after head-up tilt, in the period preceding the syncope event (i) the information stored in CBFV variability decreased significantly while the information transferred to CBFV from AP variability increased significantly; (ii) the information storage of HP was kept high but the information transferred to HP from SAP variability decreased significantly. These patterns of information processing suggest that presyncope occurs with a loss both of CB regulation, described by the reduced ability of CBFV of buffering AP fluctuations, and of CV regulation, described by the reduced baroreflex modulation from SAP to HP. We believe that the utilization of tools from the field of information dynamics may give an integrated view of the mechanisms of CB and CV regulation in normal and diseased states, and also provide a deeper understanding of findings revealed by more traditional techniques. Â© 2013 Elsevier B.V.
|Numero di pagine||7|
|Rivista||AUTONOMIC NEUROSCIENCE: BASIC & CLINICAL|
|Stato di pubblicazione||Published - 2013|
All Science Journal Classification (ASJC) codes
- Endocrine and Autonomic Systems
- Clinical Neurology
- Cellular and Molecular Neuroscience