Christine Blume

Across the consciousness continuum—from unresponsive wakefulness to sleep

Advances in the development of new paradigms as well as in neuroimaging techniques nowadays enable us to make inferences about the level of consciousness patients with disorders of consciousness (DOC) retain. They, moreover, allow to predict their probable development. Today, we know that certain brain responses (e.g., event-related potentials or oscillatory changes) to stimulation, circadian rhythmicity, the presence or absence of sleep patterns as well as measures of resting state brain activity can serve the diagnostic and prognostic evaluation process. Still, the paradigms we are using nowadays do not allow to disentangle VS/UWS and minimally conscious state (MCS) patients with the desired reliability and validity. Furthermore, even rather well-established methods have, unfortunately, not found their way into clinical routine yet. We here review current literature as well as recent findings from our group and discuss how neuroimaging methods (fMRI, PET) and particularly electroencephalography (EEG) can be used to investigate cognition in DOC or even to assess the degree of residual awareness. We, moreover, propose that circadian rhythmicity and sleep in brain-injured patients are promising fields of research in this context.

‘nparACT’ package for R: A free software tool for the non-parametric analysis of actigraphy data

For many studies, participants’ sleep-wake patterns are monitored and recorded prior to, during and following an experimental or clinical intervention using actigraphy, i.e. the recording of data generated by movements. Often, these data are merely inspected visually without computation of descriptive parameters, in part due to the lack of user-friendly software. To address this deficit, we developed a package for R Core Team [6], that allows computing several non-parametric measures from actigraphy data. Specifically, it computes the interdaily stability (IS), intradaily variability (IV) and relative amplitude (RA) of activity and gives the start times and average activity values of M10 (i.e. the ten hours with maximal activity) and L5 (i.e. the five hours with least activity). Two functions compute these ‘classical’ parameters and handle either single or multiple files. Two other functions additionally allow computing an L-value (i.e. the least activity value) for a user-defined time span termed ‘Lflex’ value. A plotting option is included in all functions. The package can be downloaded from the Comprehensive R Archives Network (CRAN). • The package ‘nparACT’ for R serves the non-parametric analysis of actigraphy data.• Computed parameters include interdaily stability (IS), intradaily variability (IV) and relative amplitude (RA) as well as start times and average activity during the 10 h with maximal and the 5 h with minimal activity (i.e. M10 and L5).

Significance of circadian rhythms in severely brain-injured patients A clue to consciousness?

Objective: To investigate the relationship between the presence of a circadian body temperature rhythm and behaviorally assessed consciousness levels in patients with disorders of consciousness (DOC; i.e., vegetative state/unresponsive wakefulness syndrome or minimally conscious state). Methods: In a cross-sectional study, we investigated the presence of circadian temperature rhythms across 6 to 7 days using external skin temperature sensors in 18 patients with DOC. Beyond this, we examined the relationship between behaviorally assessed consciousness levels and circadian rhythmicity. Results: Analyses with Lomb-Scargle periodograms revealed significant circadian rhythmicity in all patients (range 23.5–26.3 hours). We found that especially scores on the arousal subscale of the Coma Recovery Scale–Revised were closely linked to the integrity of circadian variations in body temperature. Finally, we piloted whether bright light stimulation could boost circadian rhythmicity and found positive evidence in 2 out of 8 patients. Conclusion: The study provides evidence for an association between circadian body temperature rhythms and arousal as a necessary precondition for consciousness. Our findings also make a case for circadian rhythms as a target for treatment as well as the application of diagnostic and therapeutic means at times when cognitive performance is expected to peak.

Preferential processing of emotionally and self-relevant stimuli persists in unconscious N2 sleep

HighlightsOwn names (SONs) and angry voice (AV) stimuli are salient during wakefulness.Intriguingly, SONs and AV stimuli remain salient during unconscious N2 sleep.Results suggest a ‘sentinel processing mode’ of the brain during unconscious sleep.A K‐complex‐like response indicates preferential processing of salient stimuli.Presumably, delta, theta and sigma ERS reflect the subsequent sleep‐protecting mechanism. Abstract Information processing has been suggested to depend on the current state of the brain as well as stimulus characteristics (e.g. salience). We compared processing of salient stimuli (subject’s own names [SONs] and angry voice [AV] stimuli) to processing of unfamiliar names (UNs) and neutral voice (NV) stimuli across different vigilance stages (i.e. wakefulness as well as sleep stages N1 and N2) by means of event‐related oscillatory responses during wakefulness and a subsequent afternoon nap. Our findings suggest that emotional prosody and self‐relevance drew more attentional resources during wakefulness with specifically AV stimuli being processed more strongly. During N1, SONs were more arousing than UNs irrespective of prosody. Moreover, emotional and self‐relevant stimuli evoked stronger responses also during N2 sleep suggesting a ‘sentinel processing mode’ of the brain during this state of naturally occurring unconsciousness. Finally, this initial preferential processing of salient stimuli during N2 sleep seems to be followed by an inhibitory sleep‐protecting process, which is reflected by a K‐complex‐like response.

Can self-relevant stimuli help assessing patients with disorders of consciousness?

Emotional and self-relevant stimuli are able to automatically attract attention and their use in patients suffering from disorders of consciousness (DOC) might help detecting otherwise hidden signs of cognition. We here recorded EEG in three Locked-in syndrome (LIS) and four Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) patients while they listened to the voice of a family member or an unfamiliar voice during a passive. Data indicate that, in a passive listening condition, the familiar voice induces stronger alpha desynchronization than the unfamiliar one. In an active condition, the target evoked stronger alpha desynchronization in controls, two LIS patients and one VS/UWS patient. Results suggest that self-relevant familiar voice stimuli can engage additional attentional resources and might allow the detection of otherwise hidden signs of instruction-following and thus residual awareness. Further studies are necessary to find sensitive paradigms that are suited to find subtle signs of cognition and awareness in DOC patients.

Event-related EEG power modulations and phase connectivity indicate the focus of attention in an auditory own name paradigm.

Estimating cognitive abilities in patients suffering from Disorders of Consciousness remains challenging. One cognitive task to address this issue is the so-called own name paradigm, in which subjects are presented with first names including the own name. In the active condition, a specific target name has to be silently counted. We recorded EEG during this task in 24 healthy controls, 8 patients suffering from Unresponsive Wakefulness Syndrome (UWS) and 7 minimally conscious (MCS) patients. EEG was analysed with respect to amplitude as well as phase modulations and connectivity. Results showed that general reactivity in the delta, theta and alpha frequency (event-related de-synchronisation, ERS/ERD, and phase locking between trials and electrodes) toward auditory stimulation was higher in controls than in patients. In controls, delta ERS and lower alpha ERD indexed the focus of attention in both conditions, late theta ERS only in the active condition. Additionally, phase locking between trials and delta phase connectivity was highest for own names in the passive and targets in the active condition. In patients, clear stimulus-specific differences could not be detected. However, MCS patients could reliably be differentiated from UWS patients based on their general event-related delta and theta increase independent of the type of stimulus. In conclusion, the EEG signature of the active own name paradigm revealed instruction-following in healthy participants. On the other hand, DOC patients did not show clear stimulus-specific processing. General reactivity toward any auditory input, however, allowed for a reliable differentiation between MCS and UWS patients.

Can we distinguish an “I” and “ME” during listening?—an event-related EEG study on the processing of first and second person personal and possessive pronouns

Abstract Theoretically, stimuli can be related to the self as subject (“I”) or object (“ME”) of experience. This event-related brain potential (ERP) study investigated whether listening to personal and possessive pronouns elicits different modes of self-processing regarding time-course and neural sources. Going beyond previous research, first (1PP) and second person (2PP) pronouns were included to determine the specificity of self-processing. Participants listened passively to German pronouns while the electroencephalogram was recorded. Modulation of ERPs revealed a processing advantage for the 2PP personal pronoun “du” (“you”) already in early time windows. Regarding possessive pronouns, N1 amplitudes indicated increased attention orientation to the 1PP pronoun “mein” (“my”), whereas during later time windows, processing of 1PP and 2PP possessive pronouns did not differ but differed from the third person pronoun “sein” (“his”). ERP source imaging suggests that primary sensory brain regions (auditory cortex), the insula and cortical midline structures are differentially involved into these two processing modes. The results support the idea of distinct self-processing modes (“I” and “ME”) and confirm their dynamic nature. Moreover, they demonstrate that on a neural level neither “I” or “ME” are invariantly tied to the first person, in line with the hypothesis that self-processing is relational and context-dependent.

The Voice of Anger: Oscillatory EEG Responses to Emotional Prosody.

Emotionally relevant stimuli and in particular anger are, due to their evolutionary relevance, often processed automatically and able to modulate attention independent of conscious access. Here, we tested whether attention allocation is enhanced when auditory stimuli are uttered by an angry voice. We recorded EEG and presented healthy individuals with a passive condition where unfamiliar names as well as the subject’s own name were spoken both with an angry and neutral prosody. The active condition instead, required participants to actively count one of the presented (angry) names. Results revealed that in the passive condition the angry prosody only elicited slightly stronger delta synchronization as compared to a neutral voice. In the active condition the attended (angry) target was related to enhanced delta/theta synchronization as well as alpha desynchronization suggesting enhanced allocation of attention and utilization of working memory resources. Altogether, the current results are in line with previous findings and highlight that attention orientation can be systematically related to specific oscillatory brain responses. Potential applications include assessment of non-communicative clinical groups such as post-comatose patients.

Sleep in patients with disorders of consciousness characterized by means of machine learning

Sleep has been proposed to indicate preserved residual brain functioning in patients suffering from disorders of consciousness (DOC) after awakening from coma. However, a reliable characterization of sleep patterns in this clinical population continues to be challenging given severely altered brain oscillations, frequent and extended artifacts in clinical recordings and the absence of established staging criteria. In the present study, we try to address these issues and investigate the usefulness of a multivariate machine learning technique based on permutation entropy, a complexity measure. Specifically, we used long-term polysomnography (PSG), along with video recordings in day and night periods in a sample of 23 DOC; 12 patients were diagnosed as Unresponsive Wakefulness Syndrome (UWS) and 11 were diagnosed as Minimally Conscious State (MCS). Eight hour PSG recordings of healthy sleepers (N = 26) were additionally used for training and setting parameters of supervised and unsupervised model, respectively. In DOC, the supervised classification (wake, N1, N2, N3 or REM) was validated using simultaneous videos which identified periods with prolonged eye opening or eye closure.The supervised classification revealed that out of the 23 subjects, 11 patients (5 MCS and 6 UWS) yielded highly accurate classification with an average F1-score of 0.87 representing high overlap between the classifier predicting sleep (i.e. one of the 4 sleep stages) and closed eyes. Furthermore, the unsupervised approach revealed a more complex pattern of sleep-wake stages during the night period in the MCS group, as evidenced by the presence of several distinct clusters. In contrast, in UWS patients no such clustering was found. Altogether, we present a novel data-driven method, based on machine learning that can be used to gain new and unambiguous insights into sleep organization and residual brain functioning of patients with DOC.

Continued Evaluation of Environmental Stimuli in the Absence of Consciousness suggests the Human Brain is Standing Sentinel during Sleep

While it is well-known that subject’s own names (SON) or familiar voices are salient during wakefulness, we investigate stimulus processing during sleep including N3 and REM sleep. Additionally, we investigate how sleep EEG patterns (i.e. sleep spindles and slow oscillations [SOs]) relate to stimulus processing. Using 256-channel EEG we studied stimulus processing by means of event-related oscillatory responses (de-/synchronisation, ERD/ERS) and potentials (ERPs). We varied stimulus salience by manipulating subjective (SON vs. unfamiliar name) and paralinguistic emotional relevance (familiar vs. unfamiliar voice, FV/UFV). We show that evaluation of voice familiarity continues during all NREM sleep stages and even REM sleep suggesting a ‘sentinel processing mode’ in the absence of consciousness. Especially UFV stimuli elicit larger responses in a 1-15Hz range suggesting they are salient. Unlike previously suggested sleep spindles and the negative slope of SOs do not uniformly inhibit information processing but inhibition seems to be tuned to stimulus salience.While it is a well-established finding that subject’s own names (SON) or familiar voices are salient during wakefulness, we here investigated processing of environmental stimuli during sleep including deep N3 and REM sleep. Besides the effects of sleep depth we investigated how sleep-specific EEG patterns (i.e. sleep spindles and slow oscillations [SOs]) relate to stimulus processing. Using 256-channel EEG we studied processing of auditory stimuli by means of event-related oscillatory responses (de-/ synchronisation, ERD/ERS) and potentials (ERPs) in N = 17 healthy sleepers. We varied stimulus salience by manipulating subjective (SON vs. unfamiliar name) and paralinguistic emotional relevance (familiar vs. unfamiliar voice, FV/UFV). Results reveal that evaluation of voice familiarity continues during all NREM sleep stages and even REM sleep suggesting a ‘sentinel processing mode’ of the human brain in the absence of wake-like consciousness. Especially UFV stimuli elicit larger responses in a 1-15 Hz range suggesting they continue being salient. Beyond this, we find that sleep spindles and the negative slope of SOs attenuate information processing. However, unlike previously suggested they do not uniformly inhibit information processing, but inhibition seems to be scaled to stimulus salience. Funding CB is supported by the Konrad-Adenauer-Stiftung e.V. and CB, MW and DPJH are supported by a grant from the Austrian Science Fund FWF (Y-777). CB, RdG, MW and DPJH are also supported by the Doctoral College “Imaging the Mind” (FWF; W1233-G17).