Inter-individual variability of oscillatory responses to subject's own name. A single-subject analysis

Höller, Yvonne; Kronbichler, Martin; Bergmann, Jürgen; Crone, Julia Sophia; Schmid, Elisabeth; Golaszewski, Stefan; Ladurner, G.

doi:10.1016/j.ijpsycho.2011.03.012

Cited by 15 publications

(14 citation statements)

References 57 publications

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“…With respect to power spectra, the difference between motor-imagery and rest is obvious above central, parietal, and occipital regions in healthy participants, but with a high SD in the range of the -rhythm. This inter-individual difference in activation patterns is well in line with previous research involving simple stimuli such as an oddball [36], [37], subject's own name [38], [39], but also complex tasks such as music [40], and specifically motor imagery [15], [41], in which healthy participants show contradictory patterns of activation. As a consequence, visually exploring the pattern of coherences cannot specify whether a patient was performing the task or not.…”

Section: Discussionsupporting

confidence: 89%

Comparison of EEG-Features and Classification Methods for Motor Imagery in Patients with Disorders of Consciousness

et al. 2013

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Current research aims at identifying voluntary brain activation in patients who are behaviorally diagnosed as being unconscious, but are able to perform commands by modulating their brain activity patterns. This involves machine learning techniques and feature extraction methods such as applied in brain computer interfaces. In this study, we try to answer the question if features/classification methods which show advantages in healthy participants are also accurate when applied to data of patients with disorders of consciousness. A sample of healthy participants (N = 22), patients in a minimally conscious state (MCS; N = 5), and with unresponsive wakefulness syndrome (UWS; N = 9) was examined with a motor imagery task which involved imagery of moving both hands and an instruction to hold both hands firm. We extracted a set of 20 features from the electroencephalogram and used linear discriminant analysis, k-nearest neighbor classification, and support vector machines (SVM) as classification methods. In healthy participants, the best classification accuracies were seen with coherences (mean = .79; range = .53−.94) and power spectra (mean = .69; range = .40−.85). The coherence patterns in healthy participants did not match the expectation of central modulated -rhythm. Instead, coherence involved mainly frontal regions. In healthy participants, the best classification tool was SVM. Five patients had at least one feature-classifier outcome with p0.05 (none of which were coherence or power spectra), though none remained significant after false-discovery rate correction for multiple comparisons. The present work suggests the use of coherences in patients with disorders of consciousness because they show high reliability among healthy subjects and patient groups. However, feature extraction and classification is a challenging task in unresponsive patients because there is no ground truth to validate the results.

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Section: Discussionsupporting

confidence: 89%

Comparison of EEG-Features and Classification Methods for Motor Imagery in Patients with Disorders of Consciousness

et al. 2013

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“…Several studies have investigated changes in brain activity when healthy individuals [3][4][5][6][7][8][9][10] or comatose patients [11][12][13][14][15] are exposed to SON. However, to date, no such research has been reported for patients with SMID who experienced damage to the CNS perinatally or in childhood and survived at least 4 years after injury.…”

Section: Introductionmentioning

confidence: 99%

“…Mean and standard error bars of ERSPs at the Fz electrode for the 11 control subjects for (a) high theta(6)(7)(8) at 0-800 ms after stimulus onset and (b) high alpha (10-13 Hz) at 200-400 ms after stimulus onset. *** P < 0.001; NS, not significant.…”

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Phase-locked theta activity evoked in patients with severe motor and intellectual disabilities upon hearing own names

Tamura

Karube

Mizuba

et al. 2015

Brain and Development

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“…For this investigation, we performed a group analysis and a single-subject analysis. Both analyses are important because results at the group level do not always reflect findings in the single subject (Kotchoubey et al, 2004; Holler et al, 2011) which are crucial for diagnosis in patients with DOC. Thus, we implemented two different preprocessing approaches: for group analysis, preprocessing steps included the following procedures: segmentation of the T1 image to compute the gray matter images; realignment to compensate for motion; unwarping (adjustment for movement-related artifacts); pre-coregistration of the functional images of session 2 to session 1; coregistration of the mean EPI to the participant’s gray matter image; normalization of an average image of the functional images with the segmentation parameters; data were spatially smoothed using a Gaussian Kernel of 8 mm full width at half maximum (FWHM); For single-subject statistical analysis, we did not perform normalization of the functional data to avoid artifacts induced by severe lesions.…”

Section: Methodsmentioning

confidence: 99%

Self-Related Processing and Deactivation of Cortical Midline Regions in Disorders of Consciousness

Crone¹,

Höller²,

Bergmann³

et al. 2013

Front. Hum. Neurosci.

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Self-related stimuli activate anterior parts of cortical midline regions, which normally show task-induced deactivation. Deactivation in medial posterior and frontal regions is associated with the ability to focus attention on the demands of the task, and therefore, with consciousness. Studies investigating patients with impaired consciousness, that is, patients in minimally conscious state and patients with unresponsive wakefulness syndrome (formerly vegetative state), demonstrate that these patients show responses to self-related content in the anterior cingulate cortex. However, it remains unclear if these responses are an indication for conscious processing of stimuli or are due to automatic processing. To shed further light on this issue, we investigated responses of cortical midline regions to the own and another name in 27 patients with a disorder of consciousness and compared them to task-induced deactivation. While almost all of the control subjects responding to the own name demonstrated higher activation due to the self-related content in anterior midline regions and additional deactivation, none of the responding patients did so. Differences between groups showed a similar pattern of findings. Despite the relation between behavioral responsiveness in patients and activation in response to the own name, the findings of this study do not provide evidence for a direct association of activation in anterior midline regions and conscious processing. The deficits in processing of self-referential content in anterior midline regions may rather be due to general impairments in cognitive processing and not particularly linked to impaired consciousness.

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Inter-individual variability of oscillatory responses to subject's own name. A single-subject analysis

Cited by 15 publications

References 57 publications

Comparison of EEG-Features and Classification Methods for Motor Imagery in Patients with Disorders of Consciousness

Comparison of EEG-Features and Classification Methods for Motor Imagery in Patients with Disorders of Consciousness

Phase-locked theta activity evoked in patients with severe motor and intellectual disabilities upon hearing own names

Self-Related Processing and Deactivation of Cortical Midline Regions in Disorders of Consciousness

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