Mismatch negativity and late auditory evoked potentials in comatose patients

Fischer, Catherine; Morlet, Dominique; Bouchet, Patrick; Luauté, Jacques; Jourdan, C; Salord, F

doi:10.1016/s1388-2457(99)00131-5

Cited by 231 publications

(149 citation statements)

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“…When the global effect is absent, and only an early and transient local effect is observed, interpretation must be cautious. This pattern may signal nonconscious processing, as previously observed in comatose patients (13)(14)(15) and in vegetative state patients (16,17), but also a patient who is aware but not attending. Indeed, all functional measures of conscious processing are also subject to variations of arousal, attention, and task performance (33).…”

Section: A Global Workpace Network Subtends the Conscious ''Global Esupporting

confidence: 59%

“…In addition to this temporal distinction between MMN and P3b responses, MMN (and P3a) are largely resistant to top-down and attentional effects. They can even be observed during rapid eye-movement sleep (11) and anesthesia (12), and in unconscious comatose (13)(14)(15) or vegetative state patients (16,17) or in response to visual subliminal stimuli (18,19), whereas the P3b is highly dependent on attention and conscious awareness of the stimulus (6,20).…”

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confidence: 99%

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Neural signature of the conscious processing of auditory regularities

Bekinschtein

Dehaene

Rohaut

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

592

819

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Can conscious processing be inferred from neurophysiological measurements? Some models stipulate that the active maintenance of perceptual representations across time requires consciousness. Capitalizing on this assumption, we designed an auditory paradigm that evaluates cerebral responses to violations of temporal regularities that are either local in time or global across several seconds. Local violations led to an early response in auditory cortex, independent of attention or the presence of a concurrent visual task, whereas global violations led to a late and spatially distributed response that was only present when subjects were attentive and aware of the violations. We could detect the global effect in individual subjects using functional MRI and both scalp and intracerebral event-related potentials. Recordings from 8 noncommunicating patients with disorders of consciousness confirmed that only conscious individuals presented a global effect. Taken together these observations suggest that the presence of the global effect is a signature of conscious processing, although it can be absent in conscious subjects who are not aware of the global auditory regularities. This simple electrophysiological marker could thus serve as a useful clinical tool.consciousness ͉ neuroimaging ͉ neurophysiology ͉ patients

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Section: A Global Workpace Network Subtends the Conscious ''Global Esupporting

confidence: 59%

mentioning

confidence: 99%

Neural signature of the conscious processing of auditory regularities

Bekinschtein

Dehaene

Rohaut

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

592

819

View full text Add to dashboard Cite

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“…MMN can be useful in efforts to ascertain perceptual Page 5 capabilities of the comatose patient as well as the likelihood of awakening from coma. The presence of MMN recorded during the comatose state is the best predictor of awakening within a 12-month period (Fischer et al, 1999). A positive predictive value for awakening has been reported in 100% of cases in a recent study , whereas absence of MMN was predictive of non-awakening in 84% of cases.…”

Section: Comamentioning

confidence: 88%

Event-related potentials in clinical research: Guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400

Duncan

Barry

Connolly

et al. 2009

Clinical Neurophysiology

995

845

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“…Its advantages are relatively low costs, a high temporal resolution and portability due to the small size of the recording device. Today's clinical applications (see Binnie, 1995) range from coma monitoring (Fischer et al, 1999) to research on diseases such as schizophrenia (Ford, 1999), dyslexia (Baldeweg et al, 1999), ADHD (Barry et al, 2003) and dementia (Patterson et al, 1988).…”

Section: Part I R E V I S I T I N G B C Imentioning

confidence: 99%

On robust spatial filtering of EEG in nonstationary environments

Samek

2016

It - Information Technology

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bibliography 119 I N T R O D U C T I O NVariability is the law of life, and as no two faces are the same, so no two bodies are alike, and no two individuals react alike and behave alike under the abnormal conditions which we know as disease. (Sir William Osler, 1903) T he Canadian physician Sir William Osler (1849 -1919 revolutionized the medical world of the 19th century by advocating an approach to therapy which focuses on the needs of individual patients. He recognized the great variability among individuals with respect to their physical conditions, their mental status and their responses to drugs and concluded that focusing solely on clinical signs and symptoms does not result in the most effective therapy. The development of this novel patient-centered paradigm made him the father of personalized medicine; a branch of medicine that is also very popular today due to a better understanding of the genetic influences on a person's risk of acquiring certain diseases.In the last two decades personalized approaches have also revolutionized the field of Brain-Computer Interfacing (BCI). A BCI system (see e.g. Wolpaw et al., 2002;Dornhege et al., 2007;Wolpaw and Wolpaw, 2012) aims to decode the intention of a user from recordings of brain activity and to use this information for controlling a computer application or a robotic device. Today's BCIs extract user-specific features from electroencelographic (EEG) recordings and adapt to the user's signal characteristics. This subject-centered or machine learning approach not only largely reduces the calibration time in comparison to classical BCI systems based on neurofeedback training (Kamiya et al., 1969) but also increases classification accuracy. Unfortunately, EEG responses to a stimulus or a task not only differ from subject to subject but also from trial to trial and from day to day. This change in the signal properties over time is termed the intrinsic nonstationarity of EEG (Kaplan et al., 2005) and constitutes a major challenge for data analysis and classification by violating a basic assumption of many machine learning methods, namely that data are sampled from a fixed (but unknown) distribution (Vapnik, 1998;Hastie et al., 2001). The analysis of EEG is further aggravated by the presence of artifacts in the data, e.g., eye movements, muscular activity or loose electrodes. The lack of robustness to unexpected events and the nonstationary nature of EEG are major reasons in explaining why current BCI technology is seldom used in out-of-lab scenarios and clinical practice. Since artifacts and nonstationarity can not be fully eliminated, even with the best experimental protocol, robust and invariant feature 1 2 introduction representations are required for optimal signal analysis and high classification accuracy. structure of the thesisThis thesis is divided into three parts. The first part introduces the basic concepts of motor imagery-based Brain-Computer Interfacing and discusses the advantages and limitations of several state-of-the-art spatial filtering al...

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Mismatch negativity and late auditory evoked potentials in comatose patients

Cited by 231 publications

References 22 publications

Neural signature of the conscious processing of auditory regularities

Neural signature of the conscious processing of auditory regularities

Event-related potentials in clinical research: Guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400

On robust spatial filtering of EEG in nonstationary environments

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