Elisabeth Schmid

Altered network properties of the fronto-parietal network and the thalamus in impaired consciousness☆

Recovery of consciousness has been associated with connectivity in the frontal cortex and parietal regions modulated by the thalamus. To examine this model and to relate alterations to deficits in cognitive functioning and conscious processing, we investigated topological network properties in patients with chronic disorders of consciousness recovered from coma. Resting state fMRI data of 34 patients with unresponsive wakefulness syndrome and 25 in minimally conscious state were compared to 28 healthy controls. We investigated global and local network characteristics. Additionally, behavioral measures were correlated with the local metrics of 28 regions within the fronto-parietal network and the thalamus. In chronic disorders of consciousness, modularity at the global level was reduced suggesting a disturbance in the optimal balance between segregation and integration. Moreover, network properties were altered in several regions which are associated with conscious processing (particularly, in medial parietal, and frontal regions, as well as in the thalamus). Between minimally conscious and unconscious patients the local efficiency of medial parietal regions differed. Alterations in the thalamus were particularly evident in non-conscious patients. Most of the regions affected in patients with impaired consciousness belong to the so-called ‘rich club’ of highly interconnected central nodes. Disturbances in their topological characteristics have severe impact on information integration and are reflected in deficits in cognitive functioning probably leading to a total breakdown of consciousness.

Impaired consciousness is linked to changes in effective connectivity of the posterior cingulate cortex within the default mode network

The intrinsic connectivity of the default mode network has been associated with the level of consciousness in patients with severe brain injury. Especially medial parietal regions are considered to be highly involved in impaired consciousness. To better understand what aspect of this intrinsic architecture is linked to consciousness, we applied spectral dynamic causal modeling to assess effective connectivity within the default mode network in patients with disorders of consciousness. We included 12 controls, 12 patients in minimally conscious state and 13 in vegetative state in this study. For each subject, we first defined the four key regions of the default mode network employing a subject-specific independent component analysis approach. The resulting regions were then included as nodes in a spectral dynamic causal modeling analysis in order to assess how the causal interactions across these regions as well as the characteristics of neuronal fluctuations change with the level of consciousness. The resulting pattern of interaction in controls identified the posterior cingulate cortex as the main driven hub with positive afferent but negative efferent connections. In patients, this pattern appears to be disrupted. Moreover, the vegetative state patients exhibit significantly reduced self-inhibition and increased oscillations in the posterior cingulate cortex compared to minimally conscious state and controls. Finally, the degree of self-inhibition and strength of oscillation in this region is correlated with the level of consciousness. These findings indicate that the equilibrium between excitatory connectivity towards posterior cingulate cortex and its feedback projections is a key aspect of the relationship between alterations in consciousness after severe brain injury and the intrinsic functional architecture of the default mode network. This impairment might be principally due to the disruption of the mechanisms underlying self-inhibition and neuronal oscillations in the posterior cingulate cortex.

Preserved oscillatory response but lack of mismatch negativity in patients with disorders of consciousness

OBJECTIVE The diagnostic validity of non-phase-locked oscillations (NPLOs) and mismatch negativity (MMN) in an oddball task for assessing attentional reactivity in patients with disordered consciousness was examined. METHODS Patients in a minimally conscious (MCS, n = 6) or vegetative (VS, n = 16) state and healthy controls (n = 15) were assessed. MMN and NPLOs were analyzed with single-subject, non-parametric statistics. RESULTS In 11 healthy controls and 2 VS patients, MMN was detected. More subjects showed NPLO differences in the alpha than in the theta or beta frequency ranges. In 14 healthy controls, 4 MCS patients, and 5 VS patients, lower amplitudes after deviants were found in the alpha frequency range. One healthy subject and one VS patient showed higher amplitudes after deviants. CONCLUSIONS Neither ERPs nor NPLOs could reliably distinguish MCS from VS patients. However, NPLOs were more sensitive than ERPs for detecting significantly different activity, and they possibly identified preserved processing better than ERPs. SIGNIFICANCE Intact neurophysiological attentional responses observed in the NPLOs of VS patients may indicate a need for other diagnostic techniques. Inter-individual differences in the direction of the effect should be considered as normal variance.

Comparison of EEG-features and classification methods for motor imagery in patients with disorders of consciousness.

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.

Connectivity biomarkers can differentiate patients with different levels of consciousness

OBJECTIVE In the present study, we searched for resting-EEG biomarkers that distinguish different levels of consciousness on a single subject level with an accuracy that is significantly above chance. METHODS We assessed 44 biomarkers extracted from the resting EEG with respect to their discriminative value between groups of minimally conscious (MCS, N=22) patients, vegetative state patients (VS, N=27), and - for a proof of concept - healthy participants (N=23). We applied classification with support vector machines. RESULTS Partial coherence, directed transfer function, and generalized partial directed coherence yielded accuracies that were significantly above chance for the group distinction of MCS vs. VS (.88, .80, and .78, respectively), as well as healthy participants vs. MCS (.96, .87, and .93, respectively) and VS (.98, .84, and .96, respectively) patients. CONCLUSIONS The concept of connectivity is crucial for determining the level of consciousness, supporting the view that assessing brain networks in the resting state is the golden way to examine brain functions such as consciousness. SIGNIFICANCE The present results directly show that it is possible to distinguish patients with different levels of consciousness on the basis of resting-state EEG.

Real movement vs. motor imagery in healthy subjects

Motor imagery tasks are well established procedures in brain computer interfaces, but are also used in the assessment of patients with disorders of consciousness. For testing awareness in unresponsive patients it is necessary to know the natural variance of brain responses to motor imagery in healthy subjects. We examined 22 healthy subjects using EEG in three conditions: movement of both hands, imagery of the same movement, and an instruction to hold both hands still. Single-subject non-parametric statistics were applied to the fast-Fourier transformed data. Most effects were found in the α- and β-frequency ranges over central electrodes, that is, in the μ-rhythm. We found significant power changes in 18 subjects during movement and in 11 subjects during motor imagery. In 8 subjects these changes were consistent over both conditions. The significant power changes during movement were a decrease of μ-rhythm. There were 2 subjects with an increase and 9 subjects with a decrease of μ-rhythm during imagery. α and β are the most responsive frequency ranges, but there is a minor number of subjects who show a synchronization instead of the more common desynchronization during motor imagery. A (de)synchronization of μ-rhythm can be considered to be a normal response.

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

In previous studies event-related potentials and oscillations in response to subjects own name have been analyzed extensively on group-level in healthy subjects and in patients with a disorder of consciousness. Subjects own name as a deviant produces a P3. With equiprobable stimuli, non-phase-locked alpha oscillations are smaller in response to subjects own name compared to other names or subjects own name backwards. However, little is known about replicability on a single-subject level. Seventeen healthy subjects were assessed in an own-name paradigm with equiprobable stimuli of subjects own name, another name, and subjects own name backwards. Event-related potentials and non-phase locked oscillations were analyzed with single-subject, non-parametric statistics. No consistent results were found either for ERPs or for the non-phase locked changes of oscillatory activities. Only 4 subjects showed a robust effect as expected, that is, a lower activity in the alpha-beta range to subjects own name compared to other conditions. Four subjects elicited a higher activity for subjects own name. Thus, analyzing the EEG reactivity in the own-name paradigm with equiprobable stimuli on a single-subject level yields a high variance between subjects. In future research, single-subject statistics should be applied for examining the validity of physiologic measurements in other paradigms and for examining the pattern of reactivity in patients.

Individual brain-frequency responses to self-selected music.

Music is a stimulus which may give rise to a wide range of emotional and cognitive responses. Therefore, brain reactivity to music has become a focus of interest in cognitive neuroscience. It is possible that individual preference moderates the effectof music on the brain. In the present study we examined whether there are common effects of listening to music even if each subject in a sample chooses their own piece of music. We invited 18 subjects to bring along their favorite relaxing music, and their favourite stimulating music. Additionally, a condition with tactile stimulation on the foot and a baseline condition (rest) without stimulation were used. The tactile stimulation was chosen to provide a simple, non-auditory condition which would be identical for all subjects. The electroencephalogram was recorded for each of the 3 conditions and during rest. We found responses in the alpha range mainly on parietal and occipital sites that were significant compared to baseline in 13 subjects during relaxing music, 15 subjects during activating music, and 16 subjects during tactile stimulation. Most subjects showed an alpha desynchronization in a lower alpha range followed by a synchronization in an upper frequency range. However, some subjects showed an increase in this area, whereas others showed a decrease only. In addition, many subjects showed reactivity in the beta range. Beta activity was especially increased while listening to activating music and during tactile stimulation in most subjects. We found interindividual differences in the response patterns even though the stimuli provoked comparable subjective emotions (relaxation, activation), and even if the stimulus was the same for all subjects (somatosensory stimulation). We suggest that brain responsivity to music should be examined individually by considering individual characteristics.

EEG-Response Consistency across Subjects in an Active Oddball Task

The active oddball paradigm is a candidate task for voluntary brain activation. Previous research has focused on group effects, and has largely overlooked the potential problem of interindividual differences. Interindividual variance causes problems with the interpretation of group-level results. In this study we want to demonstrate the degree of consistency in the active oddball task across subjects, in order to answer the question of whether this task is able to reliably detect conscious target processing in unresponsive patients. We asked 18 subjects to count rare targets and to ignore frequent standards and rare distractors in an auditory active oddball task. Event-related-potentials (ERPs) and time-frequency data were analyzed with permutation-t-tests on a single subject level. We plotted the group-average ERPs and time-frequency data, and evaluated the numbers of subjects showing significant differences between targets and distractors in certain time-ranges. The distinction between targets/distractors and standards was found to be significant in the time-range of the P300 in all participants. In contrast, significant differences between targets and distractors in the time-range of the P3a/b were found in 8 subjects, only. By including effects in the N1 and in a late negative component there remained 2 subjects who did not show a distinction between targets and distractors in the ERP. While time-frequency data showed prominent effects for target/distractor vs. standard, significant differences between targets and distractors were found in 2 subjects, only. The results suggest that time-frequency- and ERP-analysis of the active oddball task may not be sensitive enough to detect voluntary brain activation in unresponsive patients. In addition, we found that time-frequency analysis was even less informative than ERPs about the subject’s task performance. Despite suggesting the use of more sensitive paradigms and/or analysis techniques, the present results give further evidence that electroencephalographic research should rely more strongly on single-subject analysis because interpretations of group-effects may be misleading.

Imagine There Is No Plegia. Mental Motor Imagery Difficulties in Patients with Traumatic Spinal Cord Injury

In rehabilitation of patients with spinal cord injury (SCI), imagination of movement is a candidate tool to promote long-term recovery or to control futuristic neuroprostheses. However, little is known about the ability of patients with spinal cord injury to perform this task. It is likely that without the ability to effectively perform the movement, the imagination of movement is also problematic. We therefore examined, whether patients with SCI experience increased difficulties in motor imagery (MI) compared to healthy controls. We examined 7 male patients with traumatic spinal cord injury (aged 23–70 years, median 53) and 20 healthy controls (aged 21–54 years, median 30). All patients had incomplete SCI, with AIS (ASIA Impairment Scale) grades of C or D. All had cervical lesions, except one who had a thoracic injury level. Duration after injury ranged from 3 to 314 months. We performed the Movement Imagery Questionnaire Revised as well as the Beck Depression Inventory in all participants. The self-assessed ability of patients to visually imagine movements ranged from 7 to 36 (Md = 30) and tended to be decreased in comparison to healthy controls (ranged 16–49, Md = 42.5; W = 326.5, p = 0.055). Also, the self-assessed ability of patients to kinesthetically imagine movements (range = 7–35, Md = 31) differed significantly from the control group (range = 23–49, Md = 41; W = 337.5, p = 0.0047). Two patients yielded tendencies for depressive mood and they also reported most problems with movement imagination. Statistical analysis however did not confirm a general relationship between depressive mood and increased difficulty in MI across both groups. Patients with spinal cord injury seem to experience difficulties in imagining movements compared to healthy controls. This result might not only have implications for training and rehabilitation programs, but also for applications like brain-computer interfaces used to control neuroprostheses, which are often based on the brain signals exhibited during the imagination of movements.