Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity
In daily life, in the operating room and in the laboratory, the operational way to assess wakefulness and consciousness is through responsiveness. A number of studies suggest that the awake, conscious state is not the default behavior of an assembly of neurons, but rather a very special state of act...
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| Formato: | JOUR |
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| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_20452322_v9_n1_p_Alonso |
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todo:paper_20452322_v9_n1_p_Alonso2023-10-03T16:38:30Z Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity Alonso, L.M. Solovey, G. Yanagawa, T. Proekt, A. Cecchi, G.A. Magnasco, M.O. anesthesia induction anesthesia level article awareness classifier clinical practice controlled study ego development human human experiment patient monitoring theoretical study wakefulness In daily life, in the operating room and in the laboratory, the operational way to assess wakefulness and consciousness is through responsiveness. A number of studies suggest that the awake, conscious state is not the default behavior of an assembly of neurons, but rather a very special state of activity that has to be actively maintained and curated to support its functional properties. Thus responsiveness is a feature that requires active maintenance, such as a homeostatic mechanism to balance excitation and inhibition. In this work we developed a method for monitoring such maintenance processes, focusing on a specific signature of their behavior derived from the theory of dynamical systems: stability analysis of dynamical modes. When such mechanisms are at work, their modes of activity are at marginal stability, neither damped (stable) nor exponentially growing (unstable) but rather hovering in between. We have previously shown that, conversely, under induction of anesthesia those modes become more stable and thus less responsive, then reversed upon emergence to wakefulness. We take advantage of this effect to build a single-trial classifier which detects whether a subject is awake or unconscious achieving high performance. We show that our approach can be developed into a means for intra-operative monitoring of the depth of anesthesia, an application of fundamental importance to modern clinical practice. © 2019, The Author(s). JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_20452322_v9_n1_p_Alonso |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
anesthesia induction anesthesia level article awareness classifier clinical practice controlled study ego development human human experiment patient monitoring theoretical study wakefulness |
| spellingShingle |
anesthesia induction anesthesia level article awareness classifier clinical practice controlled study ego development human human experiment patient monitoring theoretical study wakefulness Alonso, L.M. Solovey, G. Yanagawa, T. Proekt, A. Cecchi, G.A. Magnasco, M.O. Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity |
| topic_facet |
anesthesia induction anesthesia level article awareness classifier clinical practice controlled study ego development human human experiment patient monitoring theoretical study wakefulness |
| description |
In daily life, in the operating room and in the laboratory, the operational way to assess wakefulness and consciousness is through responsiveness. A number of studies suggest that the awake, conscious state is not the default behavior of an assembly of neurons, but rather a very special state of activity that has to be actively maintained and curated to support its functional properties. Thus responsiveness is a feature that requires active maintenance, such as a homeostatic mechanism to balance excitation and inhibition. In this work we developed a method for monitoring such maintenance processes, focusing on a specific signature of their behavior derived from the theory of dynamical systems: stability analysis of dynamical modes. When such mechanisms are at work, their modes of activity are at marginal stability, neither damped (stable) nor exponentially growing (unstable) but rather hovering in between. We have previously shown that, conversely, under induction of anesthesia those modes become more stable and thus less responsive, then reversed upon emergence to wakefulness. We take advantage of this effect to build a single-trial classifier which detects whether a subject is awake or unconscious achieving high performance. We show that our approach can be developed into a means for intra-operative monitoring of the depth of anesthesia, an application of fundamental importance to modern clinical practice. © 2019, The Author(s). |
| format |
JOUR |
| author |
Alonso, L.M. Solovey, G. Yanagawa, T. Proekt, A. Cecchi, G.A. Magnasco, M.O. |
| author_facet |
Alonso, L.M. Solovey, G. Yanagawa, T. Proekt, A. Cecchi, G.A. Magnasco, M.O. |
| author_sort |
Alonso, L.M. |
| title |
Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity |
| title_short |
Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity |
| title_full |
Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity |
| title_fullStr |
Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity |
| title_full_unstemmed |
Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity |
| title_sort |
single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity |
| url |
http://hdl.handle.net/20.500.12110/paper_20452322_v9_n1_p_Alonso |
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