Some individuals who experience severe brain damage are left with disorders of consciousness. While they can appear to be awake, these individuals lack awareness of their surroundings and cannot respond to events going on around them. Few treatments are available, but a minority of patients show striking improvements in speech, alertness and movement in response to the sleeping pill zolpidem.

Although the idea of a sleeping pill increasing consciousness is paradoxical, it is possible that in patients with impaired consciousness, zolpidem reduces the activity of an area of the brain that would otherwise inhibit activity in other regions of the brain. However, the precise mechanisms by which zolpidem increases consciousness in these patients, and the reasons why only a minority of individuals respond, are unknown.

Now, Williams et al. have used electrodes attached to the scalp to measure changes in brain activity in three patients known to respond to zolpidem. These measurements showed that before the drug was taken, there were two important differences between the brain activity of the patients and that of healthy subjects: first, the patients showed brain waves of a lower frequency than any seen in healthy subjects; second, these brain waves were much more synchronized than brain activity in healthy individuals. After taking zolpidem, this synchronicity was reduced and all of the patients also showed an increase in higher frequency brain waves.

Based on the effects of zolpidem on electrical activity throughout the brain, Williams et al. propose a new model to explain the therapeutic action of the drug in some minimally conscious patients. If the correlation between brain waves and zolpidem response holds up in future studies, this relation could be used to predict which patients might benefit from the drug. A better understanding of these processes should also help us to understand, diagnose and develop new treatments for disorders of consciousness.

Induced recovery of spoken language, cognitive and motor functions following administration of zolpidem, a gamma-aminobutyric acid type A (GABA-A) subclass alpha 1 receptor positive allosteric modulator (Hambrecht-Wiedbusch et al., 2010) in severely brain-injured subjects with disorders of consciousness are rare, but well documented (Clauss et al., 2000; Brefel-Courbon et al., 2007; Cohen and Duong, 2008; Shames and Ring, 2008; Whyte, 2009; Hall et al., 2010). In some instances, behavioral improvement spans the range from only limited signs of conscious awareness to recovery of conversant language, ambulation and coordinated motor activity within an hour of administration of the medication. However, the mechanisms underlying this phenomenon are poorly understood. Because of the rarity of the phenomenon, as well as logistical impediments, only a small number of prior studies have characterized zolpidem-induced physiological changes these patients (Clauss et al., 2000; Clauss and Nel, 2006; Brefel-Courbon et al., 2007; Cohen and Duong, 2008; Shames and Ring, 2008; Whyte, 2009; Hall et al., 2010; Nyakale et al., 2010).

Here we investigate the detailed neurophysiological changes present in the resting electroencephalogram (EEG) in three patient subjects with such paradoxical behavioral facilitation in response to zolpidem and widely disparate underlying etiologies of severe brain injury and disorders of consciousness (severe hypoxic-ischemic encephalopathy, severe diffuse axonal injury and multifocal ischemic injuries). All subjects were more than 12 months post-injury and had histories of zolpidem response and regular usage of the drug for behavioral facilitation. Despite the wide differences in the etiology of brain injury across subjects, quantitative analysis of resting EEG dynamics reveals a striking commonality of spectral features in the absence of zolpidem, and stereotyped changes in these spectral quantities when the drug is administered.

Based on the specific spectral changes observed, we propose a unifying biological mechanism accounting for the observed dynamical features of the resting brain state and the changes in brain dynamics linked with zolpidem-induced behavioral facilitation.

Further, our interpretative model implies a mechanistic basis for the differences in EEG dynamics associated with the zolpidem response in subjects with global brain injury and those observed in a stroke patient (Hall et al., 2010), and offers predictions for distinguishing these two mechanisms.

Paradoxical behavioral facilitation in response to zolpidem in severely brain-injured subjects with disorders of consciousness is well-documented, but relatively rare, with only one of 15 subjects identified in a prospective study (Whyte and Myers, 2009). Here we studied three such patients with disparate etiologies of brain injury, who had very different underlying patterns of structural brain injury and mechanisms of widespread neuronal death and disconnection. Despite these differences, quantitative EEG analysis revealed strikingly consistent dynamical signatures of brain dynamics in the resting awake state, and how these dynamics were affected by zolpidem. In all subjects, resting EEG power spectra in the baseline state revealed an abnormal peak at ∼6–10 Hz and high coherence in this same frequency range across intra- and inter-hemispheric brain regions. Behavioral activation with zolpidem reliably attenuated ∼6–10 Hz power and coherence in all subjects and associated with an increase in power at ∼15–30 Hz. These findings suggest a fundamental similarity in the dynamics of brain states that are poised to elicit a zolpidem response. Below we propose a physiological basis for these common resting state dynamics identified by our EEG findings in the OFF drug state that show specific correspondence with known physiological processes. We further discuss a key prediction of this model: that changes observed in EEG spectral content during activation in the ON drug state will covary with the degree of structural and functional deafferentation of the cerebral cortex.

It is important to note that we are stopping short of proposing that a 6–10 Hz spectral peak with high spatial coherence is a predictor of zolpidem responsiveness. We suspect that the apparent rarity of the zolpidem response is not due to the incidence of this EEG feature (which is unknown), but to other factors, such as the 50-fold variations of GABA receptor subtype expression in the human population (Kang et al., 2011). Testing these ideas, however, goes far beyond the scope of the present study, as it would require a large structured, prospective, randomized clinical trial (Whyte and Myers, 2009). We argue below, however, that these EEG findings may be a general marker of a recruitable reserve that in principle may be recruited by other neuromodulatory interventions (Schiff, 2010), and not just zolpidem.

Proposed cellular mechanisms underlying broadly coherent, low frequency oscillations observed in the OFF zolpidem state

As a result of diverse mechanisms of injury, all three severely brain-injured subjects suffered widespread neuronal death and consequent deafferentation of many neurons across the cerebral cortex and subcortical structures. The implications of severe deafferentation of cortical neurons for EEG dynamics can be estimated by comparing two extremes: completely de-afferented ‘slabs’ of cortical tissue, and normal cortical tissue. In the former case (in vivo studies of completely deafferented ‘slabs’), neocortical neurons typically have an intracellular potential of ∼-70 mV and the dominant frequency of activity measured in far field potentials is ∼1 Hz (Timofeev et al., 2000). Intact, fully connected neocortical neurons have an average membrane potential in active wakeful states, that ranges from ∼−65 to −55 mV (Steriade, 2001) and the dominant frequency of far-field potentials is in the 8–12 Hz range. Given these benchmarks it is reasonable to assume that in our patient subjects, all with very significant but incomplete deafferentation, that average membrane potentials are intermediate between these conditions. In this context, the prominent low frequency peaks seen across the power spectra from anterior EEG channels and across different OFF drug baselines of ∼7.4 Hz are notable for comparison to findings from in vitro studies of spontaneous oscillations generated by neocortical pyramidal cells. Silva et al. (Silva et al., 1991) identified that nearly identical frequencies of sustained firing lasting over seconds (7.4 Hz SD +/−0.6) are produced by layer V neocortical pyramidal cells in response to very brief (4 ms) current pulses. These sustained oscillations could be initiated under physiologic conditions in vitro that maintain intrinsic membrane potentials near firing threshold at ∼−60–65 mV (Silva et al., 1991). As seen in Tables 1 and 2, an average center frequency of 7.4 Hz (∼SD +/−0.6) characterizes all but one of nine separately measured baselines across the anterior EEG channels of Subjects 1 and 2.

Thus, we propose that the markedly deafferented conditions of cortical neurons in the reduced slice preparation may reasonably approximate the markedly deafferented state of the cortex in our three subjects and that self-sustained intrinsic membrane oscillations arising from Layer V pyramidal neurons triggered by random synaptic background activity are the underlying mechanism for the origin of the ∼6–10 Hz activity present in the resting EEG at baseline. In the slice preparation, increases in membrane depolarization with stronger and more sustained injected currents produced shifts of these intrinsically generated oscillatory firing patterns toward higher frequencies (up to 12 Hz) when kept below firing threshold (Silva et al., 1991) indicating that a wider range of frequencies beyond 7.4 Hz could in principle still reflect such pathologically driven oscillations (and in Subject 3 the resting oscillations tend to be at higher frequencies as shown in Figures 1 and 3C). Moreover, fully depolarizing these neurons in the slice results in similar shifts to ∼15–30 Hz firing rates (Silva et al., 1991).

If the intrinsic properties of partially de-afferented cortical tissue accounts for the peak of EEG activity in the 6–10 Hz range, then what could account for its high levels of spatial coherence? We propose that this coherence arises from a simple straightforward dynamical mechanism: the ‘Huygens’ clock principle’ (refer to Huygens, 1665; Rosenblum and Pikovsky, 2003). According to this principle, when oscillators with similar frequencies interact weakly, stable synchronization around a consensus frequency is the generic result. Here, we hypothesize that the net effects of residual Layer V output neurons (efferent to other cortical regions either directly or via subcortical structures) constitute a weak coupling. The predicted result is widespread coherence of cortical columns at a consensus theta frequency (∼7.4 Hz), as we in fact observe in all three subjects.

We speculate that our model for common baseline EEG dynamics may also account for other widespread rhythmic oscillations that are described in the cardiac arrest and other types of severe anoxic brain injury. These oscillations are in the alpha (Young et al., 1994) and less commonly theta (3–7 Hz) frequency range. Slower frequencies and lack of a change in frequency in response to sensory stimulation are associated with worse outcomes (Young et al., 1994), consistent with the notion that this activity results from de-afferentation, and the dominant frequency range indexes its severity.

However, we do not propose that all forms of pathological rhythmic activity arise from this mechanism, only to those in which the structural brain injuries are severe and diffuse. Theta (3–7 Hz) activity has also been reported in patients with focal cortical abnormalities or neuropsychiatric disorders without widespread neuronal loss or disconnection. For example, somewhat similar increases in theta power observed in the resting MEG signal recorded from patients with Parkinson’s disease, obsessive compulsive disorder and other syndromes have been proposed to arise in the setting of less severe deafferentation and disfacilitation of thalamic neurons producing a ‘thalamocortical dysrhymia’ syndrome (Jeanmonod et al., 1996; Llinás et al., 1999). These findings are correlated with theta frequency bursting identified in the thalamus (driven by de-inactivation of low-threshold T-type calcium channels (Jeanmonod et al., 1996)) of patients with Parkinson’s disease or central pain (Jeanmonod et al., 1996; Llinás et al., 1999) who lack broad global cerebral deafferentation that characterizes our subject population with disorders of consciousness.

The distinction between global and focal injuries leading to rhythmic theta activity is important because these scenarios predict opposite effects on locally measured EEG activity in the 15–30 Hz range. Specifically, experimental and clinical studies of thalamocortical dysrrhythmia link abnormal increases in theta power to coincident abnormal increases 15–30 Hz activity produced by lateral inhibition in the cortex (‘edge effect’, Llinás et al., 1999; Llinás et al., 2005). Of note, the linkage of elevated 4–10 Hz and 15–30 Hz activity has been observed in a study of a zolpidem responsive stroke patient subject (Hall et al., 2010). Hall et al.(2010) studied MEG signals in a fully conscious, alert, and cognitively normal patient subject with mild aphasia and diminished sensorimotor integration ; these investigators reported that zolpidem administration produced similar changes of power suppression in co-localized areas of abnormally increased 4–10 Hz activity and increased 15–30 Hz activity in the resting MEG signal measured near the boundaries of a large stroke lesion within the damaged hemisphere. This suppression of increased high frequency power with zolpidem is exactly opposite to the changes observed in ∼15–40 Hz power in our subjects and indicates that a different mechanism underlies the changes seen in the present study, compared to that underlying the resting MEG activity in the Hall et al. subject (Hall et al., 2010). In the latter subject, global cerebral structures, including both thalami, remained intact and the patient’s state of consciousness was normal (and there also was no history of a preceding disorder of consciousness). Moreover, in the Hall et al. study, no increases were observed in ∼15–40 Hz power outside of MEG channels with abnormal 3–7 Hz power (where ∼15–40 Hz suppressed with zolpidem administration). Since the elevated theta and beta activity seen in the Hall et al. study was focal, it is more likely to be due to bursting of a localized set of deafferented thalamic neurons (i.e., thalamocortical dysrhythmia), than to widespread cortical de-afferentation.

To produce thalamocortical dysrhythmia, low-threshold T-type calcium channels must be de-inactivated (Jeanmonod et al., 1996; Llinás et al., 1999, 2005). This is far more probable to arise in this setting with a more locally deafferented thalamus in largely structurally intact brain. Taken together with the model proposed above, the distinct pattern of spectral changes observed in the Hall et al. patient leads to a prediction concerning the substrate of the pathological ∼3–7 Hz EEG oscillations in patients with severe brain injuries. In our subjects—with a widely coherent theta rhythm—we expect that thalamic activity is severely suppressed and not generating widespread bursting activity. In contrast, when focal ∼3–7 Hz and ∼15–40 Hz oscillations coexist (as in the Hall et al. patient [Hall et al., 2010]), we hypothesize that the thalamus is not globally suppressed, and that instead, there is bursting due to focal thalamic deafferentation. The former expectation is supported by metabolic imaging studies in Subject 2, (Figure 8, Table 3), and other studies in awake severely brain-injured subjects that included direct measurement of thalamic activity that demonstrated loss of central thalamus firing activity (Giacino et al., 2012).

Figure 8

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Table 3

Region	Left(%)	Right(%)
Mesial frontal	139	146
Lateral frontal	166	183
Calcarine	145	153
Striatum	156	156
Thalamus	148	127

In addition to the thalamocortical dysrhythmia model of 6–10 Hz activity, other theoretical models of the expression of these rhythms in the corticothalamic system exist based on network dynamics (e.g., Ching et al., 2011; Drover et al., 2011; Hughes et al., 2004; Robinson et al., 2002). However, these models do not include gross alterations in physiological profiles of neurons in severely-injured brains with average neuronal membrane potentials remaining well below firing thresholds and likely do not capture the relevant physiological conditions present in our subjects. While an intrinsic cortical mechanism appears to be sufficient to account for our observations, such independent or interacting contributions of network mechanisms linked to thalamocortical projections ultimately cannot be conclusively excluded.

Subjects 1 and 2 were admitted to the inpatient neurology unit at New York Presbyterian Hospital—Weill Cornell Campus for several days under an IRB-approved natural history study of recovery following severe brain injuries. For each subject, 24 hr video EEG were obtained while they received a continuation of their at home medication regimens. Zolpidem 10 mg was administered crushed, in solution via syringe one to three times daily by mouth for subject 1 and via percutaneous endoscopic gastrostomy (PEG) tube for subject 2. The resultant EEG recordings were reviewed for each subject, and EEG segments of 3 s duration that were artifact-free in the analyzed channels were identified extracted from the hour before and each of the first 4 hr after each administration of the drug, for each administration studied (four doses in Subject 1, five doses in Subject 2). Subject 3 underwent quantitative behavioral evaluations and study with high density EEG in their home (performed by investigators from University of Liege, Belgium) before and 20 min after taking zolpidem. Zolpidem 10 mg was administered per nasogastric tube. PET studies for ON and OFF drug states were obtained for Subject 1 and 2 but only reported for Subject 2 in ‘Clinical histories’ here as Subject 1’s OFF drug study was severely motion corrupted and reliable measurements could not be obtained. For subject 2, FDG-PET studies in both the zolpidem-naive state and 30–90 min after administration of the drug were obtained 24 hr apart at the same time of day with equivalent fasting serum glucose levels of 81 and 80 mg/dl (see below for details). All procedures done in this study were in compliance with the Declaration of Helsinki.

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Author details

1. Shawniqua T Williams

   Department of Neurology and Neuroscience, Weill Cornell Medical College, New York, United States

   Contribution

   STW, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

2. Mary M Conte

   1. Department of Neurology and Neuroscience, Weill Cornell Medical College, New York, United States
   2. Brain Mind Research Institute, Weill Cornell Medical College, New York, United States

   Contribution

   MMC, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

3. Andrew M Goldfine

   Department of Neurology and Neuroscience, Weill Cornell Medical College, New York, United States

   Contribution

   AMG, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

4. Quentin Noirhomme

   1. Coma Science Group, Cyclotron Research Centre, University of Liège and University Hospital of Liège, Liège, Belgium
   2. Neurology Department, University of Liège and University Hospital of Liège, Liège, Belgium

   Contribution

   QN, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

5. Olivia Gosseries

   1. Coma Science Group, Cyclotron Research Centre, University of Liège and University Hospital of Liège, Liège, Belgium
   2. Neurology Department, University of Liège and University Hospital of Liège, Liège, Belgium

   Contribution

   OG, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

6. Marie Thonnard

   1. Coma Science Group, Cyclotron Research Centre, University of Liège and University Hospital of Liège, Liège, Belgium
   2. Neurology Department, University of Liège and University Hospital of Liège, Liège, Belgium

   Contribution

   MT, Acquisition of data, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

7. Bradley Beattie

   Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, United States

   Contribution

   BB, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

8. Jennifer Hersh

   Division of Medical Ethics, Weill Cornell Medical College, New York, United States

   Contribution

   JH, Acquisition of data, Contributed unpublished essential data or reagents

   Competing interests

   The authors declare that no competing interests exist.

9. Douglas I Katz

   Brain Injury Program, Braintree Rehabilitation Hospital, Boston University School of Medicine, Braintree, United States

   Contribution

   DIK, Drafting or revising the article, Contributed unpublished essential data or reagents

   Competing interests

   The authors declare that no competing interests exist.

10. Jonathan D Victor

    1. Department of Neurology and Neuroscience, Weill Cornell Medical College, New York, United States
    2. Brain Mind Research Institute, Weill Cornell Medical College, New York, United States

    Contribution

    JDV, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    The authors declare that no competing interests exist.

11. Steven Laureys

    1. Coma Science Group, Cyclotron Research Centre, University of Liège and University Hospital of Liège, Liège, Belgium
    2. Neurology Department, University of Liège and University Hospital of Liège, Liège, Belgium

    Contribution

    SL, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    The authors declare that no competing interests exist.

12. Nicholas D Schiff

    1. Department of Neurology and Neuroscience, Weill Cornell Medical College, New York, United States
    2. Brain Mind Research Institute, Weill Cornell Medical College, New York, United States

    Contribution

    NDS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    For correspondence

    nds2001@med.cornell.edu

    Competing interests

    The authors declare that no competing interests exist.

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