Consciousness is a multidimensional construct with no widely accepted definition. Especially in pathological conditions, it is less clear what exactly is meant by (un) consciousness, how it can be reliably observed or measured. Here, we aim at (i) bringing together state of the art approaches to classification of single patients suffering from disorders of consciousness by means of motor-independent assessment of consciousness states with electrophysiology and functional neuroimaging, (ii) showing how each proposed metric translates into clinical practice and (iii) raising a discussion on the ethical aspects of consciousness measurements. We realize that when dealing with patients some issues commonly pertain to each methodology discussed here, such as the overall clinical condition, clinical heterogeneity, and diagnostic uncertainty. When predicting patients' diagnosis, though, each method adopts a different approach to determine (a) a "gold standard" of the benchmark population upon which the metric is computed and (b) the generalization and replicability in the attempt to avoid overfitting. From an applied ethics perspective, the focus is, hence, on knowing what one is measuring and on the validity of measurements. We conclude that, when searching for consciousness in pathological conditions, confident diagnosis can be based on the use of probabilistic predictions as well as on accumulative evidence stemming from multiple non-overlapping assessments with different modalities. A framework which will regulate the application order of these techniques (balancing their availability, sensitivity, and specificity, based on underlying clinical assumptions about a patient's conscious state), is expected to ameliorate clinical management and further inform on the critical patterns of (un) consciousness.

Measuring states of pathological (un)consciousness : research dimensions, clinical applications, and ethics / A. Demertzi, J.D. Sitt, S. Sarasso, W. Pinxten. - In: NEUROSCIENCE OF CONSCIOUSNESS. - ISSN 2057-2107. - 3:1(2017), pp. nix010.1-nix010.13. [10.1093/nc/nix010]

Measuring states of pathological (un)consciousness : research dimensions, clinical applications, and ethics

S. Sarasso
Penultimo
;
2017

Abstract

Consciousness is a multidimensional construct with no widely accepted definition. Especially in pathological conditions, it is less clear what exactly is meant by (un) consciousness, how it can be reliably observed or measured. Here, we aim at (i) bringing together state of the art approaches to classification of single patients suffering from disorders of consciousness by means of motor-independent assessment of consciousness states with electrophysiology and functional neuroimaging, (ii) showing how each proposed metric translates into clinical practice and (iii) raising a discussion on the ethical aspects of consciousness measurements. We realize that when dealing with patients some issues commonly pertain to each methodology discussed here, such as the overall clinical condition, clinical heterogeneity, and diagnostic uncertainty. When predicting patients' diagnosis, though, each method adopts a different approach to determine (a) a "gold standard" of the benchmark population upon which the metric is computed and (b) the generalization and replicability in the attempt to avoid overfitting. From an applied ethics perspective, the focus is, hence, on knowing what one is measuring and on the validity of measurements. We conclude that, when searching for consciousness in pathological conditions, confident diagnosis can be based on the use of probabilistic predictions as well as on accumulative evidence stemming from multiple non-overlapping assessments with different modalities. A framework which will regulate the application order of these techniques (balancing their availability, sensitivity, and specificity, based on underlying clinical assumptions about a patient's conscious state), is expected to ameliorate clinical management and further inform on the critical patterns of (un) consciousness.
disorders of consciousness; classification; electrophysiology; TMS; functional neuroimaging; neuroethics
Settore BIO/09 - Fisiologia
2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/528430
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