Article

Detecting Awareness in the Vegetative State

University of Cambridge, Cambridge, England, United Kingdom
Science (Impact Factor: 33.61). 10/2006; 313(5792):1402. DOI: 10.1126/science.1130197
Source: PubMed

ABSTRACT

We used functional magnetic resonance imaging to demonstrate preserved conscious awareness in a patient fulfilling the criteria
for a diagnosis of vegetative state. When asked to imagine playing tennis or moving around her home, the patient activated
predicted cortical areas in a manner indistinguishable from that of healthy volunteers.

    • "Some studies, however , extend standard statistical analysis at the single-subject level with expert visual inspection (Stender et al., 2014) or prior hypotheses (for example, Owen et al., 2006; Schnakers et al., 2008; Monti et al., 2010). For example, Owen and colleagues (Owen et al., 2006) instructed a patient to alternate 30-second periods of mental imagery of playing tennis with 30-second periods of rest following a block-design protocol. A single trial consisted of 5 rest vs. imagery cycles. "
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    ABSTRACT: Given the fact that clinical bedside examinations can have a high rate of misdiagnosis, machine learning techniques based on neuroimaging and electrophysiological measurements are increasingly being considered for comatose patients and patients with unresponsive wakefulness syndrome, a minimally conscious state or locked-in syndrome. Machine learning techniques have the potential to move from group-level statistical results to personalized predictions in a clinical setting. They have been applied for the purpose of (1) detecting changes in brain activation during functional tasks, equivalent to a behavioral command-following test and (2) estimating signs of consciousness by analyzing measurement data obtained from multiple subjects in resting state. In this review, we provide a comprehensive overview of the literature on both approaches and discuss the translation of present findings to clinical practice. We found that most studies struggle with the difficulty of establishing a reliable behavioral assessment and fluctuations in the patient's levels of arousal. Both these factors affect the training and validation of machine learning methods to a considerable degree. In studies involving more than 50 patients, small to moderate evidence was found for the presence of signs of consciousness or good outcome, where one study even showed strong evidence for good outcome.
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    • "Developing reliable and valid behavioral measures for assessment is challenging due to the severity of disability typical of the population: a combination of motor, sensory, and cognitive impairments can mask residual functioning, thus risking misdiagnosis. The auditory modality has been the focus of greater empirical inquiry due to evidence that it is the more sensitive modality for identifying awareness (Gill-Thwaites & Munday, 1999; Owen et al., 2005), provided by clinical reports of persons with DOC who have demonstrated cognitive capacity through the auditory modality even in the absence of movement and language (Giacino et al., 2009; Owen et al., 2006). Despite the increased evidence for using auditory stimuli to assess awareness, the existing standardized measures for DOC populations fail to address auditory responsiveness adequately (Lichtensztejn, Macchi, & Lischinsky, 2014; Magee, Siegert, Daveson, Lenton-Smith, & Taylor, 2014). "

    No preview · Article · Dec 2015 · Journal of music therapy
    • "Developing reliable and valid behavioral measures for assessment is challenging due to the severity of disability typical of the population: a combination of motor, sensory, and cognitive impairments can mask residual functioning, thus risking misdiagnosis. The auditory modality has been the focus of greater empirical inquiry due to evidence that it is the more sensitive modality for identifying awareness (Gill-Thwaites & Munday, 1999; Owen et al., 2005), provided by clinical reports of persons with DOC who have demonstrated cognitive capacity through the auditory modality even in the absence of movement and language (Giacino et al., 2009; Owen et al., 2006). Despite the increased evidence for using auditory stimuli to assess awareness, the existing standardized measures for DOC populations fail to address auditory responsiveness adequately (Lichtensztejn, Macchi, & Lischinsky, 2014; Magee, Siegert, Daveson, Lenton-Smith, & Taylor, 2014). "
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    ABSTRACT: Background: Prolonged Disorders of Consciousness (PDOC) describes a population where a consciousness disorder has persisted for at least four weeks post injury but is still under investigation. Complex motor, sensory, communication, and cognitive impairments cause challenges with diagnosis, assessment, and intervention planning. Developing sensitive, reliable, and valid measures is a central concern. The auditory modality is the most sensitive for identifying awareness; however, the current standardized behavioral measures fail to provide adequate screening and measurement of auditory responsiveness. The Music Therapy Assessment Tool for Awareness in Disorders of Consciousness (MATADOC) is a recently standardized measure for assessment with PDOC; however, psychometric values for two of its subscales require examination.
    No preview · Article · Dec 2015 · Journal of music therapy
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