Toward operational architectonics of consciousness: basic evidence from patients with severe cerebral injuries

Patients with Disorders of Consciousness: Are They Nonconscious, Unconscious, or Subconscious? Expanding the Discussion

Unprecedented advancements in the diagnosis and treatment of patients with disorders of consciousness (DoC) have given rise to ethical questions about how to recognize and respect autonomy and a sense of agency of the personhood when those capacities are themselves disordered, as they typically are in patients with DoC. At the intersection of these questions rests the distinction between consciousness and unconsciousness. Indeed, evaluations of consciousness levels and capacity for recovery have a significant impact on decisions regarding whether to discontinue or prolong life-sustaining therapy for DoC patients. However, in the unconsciousness domain, there is the confusing array of terms that are regularly used interchangeably, making it quite challenging to comprehend what unconsciousness is and how it might be empirically grounded. In this opinion paper, we will provide a brief overview of the state of the field of unconsciousness and show how a rapidly evolving electroencephalogram (EEG) neuroimaging technique may offer empirical, theoretical, and practical tools to approach unconsciousness and to improve our ability to distinguish consciousness from unconsciousness and also nonconsciousness with greater precision, particularly in cases that are borderline (as is typical in patients with DoC). Furthermore, we will provide a clear description of three distant notions of (un)consciousness (unconsciousness, nonconsciousness, and subconsciousness) and discuss how they relate to the experiential selfhood which is essential for comprehending the moral significance of what makes life worth living.

A guideline for linking brain wave findings to the various aspects of discrete perception

Brain waves, determined by electrical and magnetic brain recordings (e.g., EEG and MEG), and fluctuating behavioral responses, determined by response time or accuracy measures, are frequently taken to support discrete perception. For example, it has been proposed that humans experience only one conscious percept per brain wave (e.g., during one alpha cycle). However, the proposed link between brain waves and discrete perception is typically rather vague. More importantly, there are many models and aspects of discrete perception and it is often not apparent in what theoretical framework brain wave findings are interpreted and to what specific aspects of discrete perception they relate. Here, we review different approaches to discrete perception and highlight issues with particular interpretations. We then discuss how certain findings on brain waves may relate to certain aspects of discrete perception. The main purpose of this meta‐contribution is to give a short overview of discrete models of perception and to illustrate the need to make explicit what aspects of discrete theories are addressed by what aspects of brain wave findings.

Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group

The analysis of spontaneous EEG activity and evoked potentialsis a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). Thepast few years have witnessed an unprecedented surge in EEG-related research applied to the prediction and detection of recovery of consciousness after severe brain injury,opening up the prospect that new concepts and tools may be available at the bedside. This paper provides a comprehensive, critical overview of bothconsolidated and investigational electrophysiological techniquesfor the prognostic and diagnostic assessment of DoC.We describe conventional clinical EEG approaches, then focus on evoked and event-related potentials, and finally we analyze the potential of novel research findings. In doing so, we (i) draw a distinction between acute, prolonged and chronic phases of DoC, (ii) attempt to relate both clinical and research findings to the underlying neuronal processes and (iii) discuss technical and conceptual caveats.The primary aim of this narrative review is to bridge the gap between standard and emerging electrophysiological measures for the detection and prediction of recovery of consciousness. The ultimate scope is to provide a reference and common ground for academic researchers active in the field of neurophysiology and clinicians engaged in intensive care unit and rehabilitation.

Measuring the Complexity of Consciousness

The grand quest for a scientific understanding of consciousness has given rise to many new theoretical and empirical paradigms for investigating the phenomenology of consciousness as well as clinical disorders associated to it. A major challenge in this field is to formalize computational measures that can reliably quantify global brain states from data. In particular, information-theoretic complexity measures such as integrated information have been proposed as measures of conscious awareness. This suggests a new framework to quantitatively classify states of consciousness. However, it has proven increasingly difficult to apply these complexity measures to realistic brain networks. In part, this is due to high computational costs incurred when implementing these measures on realistically large network dimensions. Nonetheless, complexity measures for quantifying states of consciousness are important for assisting clinical diagnosis and therapy. This article is meant to serve as a lookup table of measures of consciousness, with particular emphasis on clinical applicability. We consider both, principle-based complexity measures as well as empirical measures tested on patients. We address challenges facing these measures with regard to realistic brain networks, and where necessary, suggest possible resolutions.

Large-Scale Brain Simulation and Disorders of Consciousness. Mapping Technical and Conceptual Issues

Modeling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain's operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate the plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders of consciousness (DOCs), e.g., Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State. Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs.

Network Properties in Transitions of Consciousness during Propofol-induced Sedation

Reliable electroencephalography (EEG) signatures of transitions between consciousness and unconsciousness under anaesthesia have not yet been identified. Herein we examined network changes using graph theoretical analysis of high-density EEG during patient-titrated propofol-induced sedation. Responsiveness was used as a surrogate for consciousness. We divided the data into five states: baseline, transition into unresponsiveness, unresponsiveness, transition into responsiveness, and recovery. Power spectral analysis showed that delta power increased from responsiveness to unresponsiveness. In unresponsiveness, delta waves propagated from frontal to parietal regions as a traveling wave. Local increases in delta connectivity were evident in parietal but not frontal regions. Graph theory analysis showed that increased local efficiency could differentiate the levels of responsiveness. Interestingly, during transitions of responsive states, increased beta connectivity was noted relative to consciousness and unconsciousness, again with increased local efficiency. Abrupt network changes are evident in the transitions in responsiveness, with increased beta band power/connectivity marking transitions between responsive states, while the delta power/connectivity changes were consistent with the fading of consciousness using its surrogate responsiveness. These results provide novel insights into the neural correlates of these behavioural transitions and EEG signatures for monitoring the levels of consciousness under sedation.

Changes in Standard Electroencephalograms Parallel Consciousness Improvements in Patients With Unresponsive Wakefulness Syndrome

OBJECTIVE

To identify changes in the standard electroencephalograms (EEGs) of patients with unresponsive wakefulness syndrome (UWS) who did or did not recover consciousness 6 months after admission to a rehabilitation department.

DESIGN

Prospective cohort study.

SETTING

Unit for severe acquired brain injuries.

PARTICIPANTS

Consecutive patients with UWS (N=28).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

EEG amplitude (reduced or normal), dominant frequency (alpha, theta, or delta), and reactivity (absent or present) were scored at admission and 6 months later. The cumulative Amplitude-Frequency-Reactivity score was evaluated. Clinical assessments were made using the Coma Recovery Scale-Revised.

RESULTS

Sixteen (57.1%) of the 28 patients with UWS recovered consciousness after 6 months, while 12 patients (42.9%) did not recover consciousness. EEG improvements occurred in 14 patients with consciousness recovery (87.5%) and 2 patients without consciousness recovery (16.7%) only. Improvements in EEG dominant frequency (from the theta to the alpha band or from the delta to the theta band), reappearance of EEG reactivity, and Amplitude-Frequency-Reactivity score increase (P<.01) differentiated patients with consciousness improvement from those without consciousness improvement. Six months after admission for rehabilitation, patients with EEG improvements showed higher Coma Recovery Scale-Revised scores than did those without EEG changes (P<.01).

CONCLUSIONS

Most patients who emerge from UWS demonstrate improvement in basic EEG characteristics over time. EEG changes in patients with UWS may aid in the timely recognition of patients transitioning into a minimally conscious state.

Long-Term (Six Years) Clinical Outcome Discrimination of Patients in the Vegetative State Could be Achieved Based on the Operational Architectonics EEG Analysis: A Pilot Feasibility Study

Electroencephalogram (EEG) recordings are increasingly used to evaluate patients with disorders of consciousness (DOC) or assess their prognosis outcome in the short-term perspective. However, there is a lack of information concerning the effectiveness of EEG in classifying long-term (many years) outcome in chronic DOC patients. Here we tested whether EEG operational architectonics parameters (geared towards consciousness phenomenon detection rather than neurophysiological processes) could be useful for distinguishing a very long-term (6 years) clinical outcome of DOC patients whose EEGs were registered within 3 months post-injury. The obtained results suggest that EEG recorded at third month after sustaining brain damage, may contain useful information on the long-term outcome of patients in vegetative state: it could discriminate patients who remain in a persistent vegetative state from patients who reach a minimally conscious state or even recover a full consciousness in a long-term perspective (6 years) post-injury. These findings, if confirmed in further studies, may be pivotal for long-term planning of clinical care, rehabilitative programs, medical-legal decisions concerning the patients, and policy makers.

Spherical Harmonics Reveal Standing EEG Waves and Long-Range Neural Synchronization during Non-REM Sleep

Previous work from our lab has demonstrated how the connectivity of brain circuits constrains the repertoire of activity patterns that those circuits can display. Specifically, we have shown that the principal components of spontaneous neural activity are uniquely determined by the underlying circuit connections, and that although the principal components do not uniquely resolve the circuit structure, they do reveal important features about it. Expanding upon this framework on a larger scale of neural dynamics, we have analyzed EEG data recorded with the standard 10–20 electrode system from 41 neurologically normal children and adolescents during stage 2, non-REM sleep. We show that the principal components of EEG spindles, or sigma waves (10–16 Hz), reveal non-propagating, standing waves in the form of spherical harmonics. We mathematically demonstrate that standing EEG waves exist when the spatial covariance and the Laplacian operator on the head's surface commute. This in turn implies that the covariance between two EEG channels decreases as the inverse of their relative distance; a relationship that we corroborate with empirical data. Using volume conduction theory, we then demonstrate that superficial current sources are more synchronized at larger distances, and determine the characteristic length of large-scale neural synchronization as 1.31 times the head radius, on average. Moreover, consistent with the hypothesis that EEG spindles are driven by thalamo-cortical rather than cortico-cortical loops, we also show that 8 additional patients with hypoplasia or complete agenesis of the corpus callosum, i.e., with deficient or no connectivity between cortical hemispheres, similarly exhibit standing EEG waves in the form of spherical harmonics. We conclude that spherical harmonics are a hallmark of spontaneous, large-scale synchronization of neural activity in the brain, which are associated with unconscious, light sleep. The analogy with spherical harmonics in quantum mechanics suggests that the variances (eigenvalues) of the principal components follow a Boltzmann distribution, or equivalently, that standing waves are in a sort of “thermodynamic” equilibrium during non-REM sleep. By extension, we speculate that consciousness emerges as the brain dynamics deviate from such equilibrium.

The Chief Role of Frontal Operational Module of the Brain Default Mode Network in the Potential Recovery of Consciousness from the Vegetative State: A Preliminary Comparison of Three Case Reports

It has been argued that complex subjective sense of self is linked to the brain default-mode network (DMN). Recent discovery of heterogeneity between distinct subnets (or operational modules - OMs) of the DMN leads to a reconceptualization of its role for the experiential sense of self. Considering the recent proposition that the frontal DMN OM is responsible for the first-person perspective and the sense of agency, while the posterior DMN OMs are linked to the continuity of 'I' experience (including autobiographical memories) through embodiment and localization within bodily space, we have tested in this study the hypothesis that heterogeneity in the operational synchrony strength within the frontal DMN OM among patients who are in a vegetative state (VS) could inform about a stable self-consciousness recovery later in the course of disease (up to six years post-injury). Using EEG operational synchrony analysis we have demonstrated that among the three OMs of the DMN only the frontal OM showed important heterogeneity in VS patients as a function of later stable clinical outcome. We also found that the frontal DMN OM was characterized by the process of active uncoupling (stronger in persistent VS) of operations performed by the involved neuronal assemblies.

Intrathecal baclofen: effects on spasticity, pain, and consciousness in disorders of consciousness and locked-in syndrome

Disorders of consciousness (DOCs) include coma, vegetative state (VS), and minimally conscious state (MCS). Coma is characterized by impaired wakefulness and consciousness, while VS and MCS are defined by lacking or discontinuous consciousness despite recovered wakefulness. Conversely, locked-in syndrome (LIS) is characterized by quadriplegia and lower cranial nerve paralysis with preserved consciousness. Intrathecal baclofen (ITB) is a useful treatment to improve spasticity both in patients with DOCs and LIS. Moreover, it supports the recovery of consciousness in some patients with VS or MCS. The precise mechanism underlying this recovery has not yet been elucidated. It has been hypothesized that ITB may act by reducing the overload of dysfunctional sensory stimuli reaching the injured brain or by stabilizing the imbalanced circadian rhythms. Although the current indication of ITB is the management of severe spasticity, its potential use in speeding the recovery of consciousness merits further investigation.

Autonomic correlates of seeing one's own face in patients with disorders of consciousness

The ability to recognize one's own face is a hallmark of self-awareness. In healthy subjects, the sympathetic skin response evoked by self-face recognition has a greater area under the curve of the signal than responses evoked by other visual stimuli. We evaluated the sympathetic skin responses evoked by self-face images and by six other visual stimuli (conditions) in 15 patients with severe disorders of consciousness and in 15 age-matched healthy subjects. Under all conditions, the evoked area of the sympathetic skin response was smaller in patients with unresponsive wakefulness syndrome, intermediate in patients in a minimally conscious state, and greater in healthy subjects. In patients with unresponsive wakefulness syndrome, no differences were found between the sympathetic skin response area evoked by self-face images and those evoked by other conditions. In patients in a minimally conscious state, the area of the sympathetic skin response evoked by self-face presentation was greater than those evoked by other conditions, even if statistical significance was reached only in the comparison to other stimuli not involving a real face. This finding may be due to the inability of these patients to differentiate their own face from those of others. Taken together, these results probably reflect a varying level of self-awareness between patients with unresponsive wakefulness syndrome and patients in a minimally conscious state, and suggest that the autonomic correlate of self-awareness may have some diagnostic implications for these patients.

EEG-guided meditation: A personalized approach

The therapeutic potential of meditation for physical and mental well-being is well documented, however the possibility of adverse effects warrants further discussion of the suitability of any particular meditation practice for every given participant. This concern highlights the need for a personalized approach in the meditation practice adjusted for a concrete individual. This can be done by using an objective screening procedure that detects the weak and strong cognitive skills in brain function, thus helping design a tailored meditation training protocol. Quantitative electroencephalogram (qEEG) is a suitable tool that allows identification of individual neurophysiological types. Using qEEG screening can aid developing a meditation training program that maximizes results and minimizes risk of potential negative effects. This brief theoretical-conceptual review provides a discussion of the problem and presents some illustrative results on the usage of qEEG screening for the guidance of mediation personalization.

EEG predictors of outcome in patients with disorders of consciousness admitted for intensive rehabilitation

OBJECTIVE

This study examined the prognostic value of standard EEG in patients with unresponsive wakefulness syndrome (UWS) or in a minimally conscious state (MCS).

METHODS

EEGs recorded at admission in 106 patients with UWS or in a MCS were analyzed retrospectively. EEG amplitude, dominant frequency, and reactivity to stimuli were correlated to patient outcomes according to the Coma Recovery Scale Revised (CRS-R). In 101 patients, data were integrated to generate a novel Amplitude-Frequency-Reactivity (AFR) scale, with scores ranging from 3 to 7.

RESULTS

Patients with reduced amplitudes showed less improvement in CRS-R scores at 3 months compared to patients with normal amplitudes. Delta, theta, and alpha frequencies were associated with the least, intermediate, and the greatest improvement in CRS-R scores, respectively. Patients with EEG reactivity showed greater improvements in CRS-R scores than patients without reactivity. The AFR scores for these patients were correlated with outcomes.

CONCLUSIONS

Reduced EEG amplitudes and delta frequencies correlated with worse clinical outcomes, while alpha frequencies and reactivity correlated with better outcomes. AFR scores allowed more delineated descriptions of outcomes in patients with normal amplitude, theta frequency, and no reactivity.

SIGNIFICANCE

Standard EEG descriptors are related to the 3-month outcomes in patients with disorders of consciousness.

The perception of pain and its management in disorders of consciousness

One of the most controversial issues in the management of patients in a vegetative state or a minimally conscious state concerns their hypothetical capacity to continue to experience pain despite an apparent absence of self- and environmental awareness. Recent functional neuroimaging studies have shown a greater perception of pain in patients in minimally conscious state compared with patients in vegetative state, suggesting the possible involvement of preserved cognitive mechanisms in the process of pain modulation in the former. In addition, a subgroup of patients might continue to experience some elementary emotional and affective feelings, as suggested by the reported activation of specific cerebral areas in response to situations, which commonly generate empathy. However, the available evidence is not sufficient to draw conclusions about the presence or absence of pain experience in patients with disorders of consciousness. Future studies should contribute to a better understanding of which central neural pathways are involved in the perception and modulation of pain in healthy subjects and in patients with severe brain injuries. Such studies should thus also improve our know-how about pain management in this particularly challenging group of patients.

Assessing learning as a possible sign of consciousness in post-coma persons with minimal responsiveness

A learning test procedure based on operant principles may be useful in the diagnosis (and eventually rehabilitation) of post-coma persons with minimal responsiveness. This study was aimed at extending the evaluation of such a procedure with seven participants who presented with very limited behavior and apparently severe disorders of consciousness. The procedure was evaluated through an ABACB design, in which A represented baseline phases without stimulation, B intervention phases with brief stimulation periods contingent on specific responses of the participants, and C a control phase in which stimulation was available all the time. Increased responding during the B phases, as opposed to the A and C phases, was taken to indicate learning and possibly a non-reflective expression of phenomenal consciousness. All participants were also evaluated with the coma recovery scale-revised (CRS-R) prior to the start of the learning test procedure and at the end of it. The results of the learning test showed that all participants had significantly higher responding levels during the B phases. The CRS-R scores suggested minimally conscious state for four of them prior to the learning test and for five of them after the completion of the learning test. The implications of the findings are discussed in terms of potential and time cost of the learning test.

Subgraph "backbone" analysis of dynamic brain networks during consciousness and anesthesia

General anesthesia significantly alters brain network connectivity. Graph-theoretical analysis has been used extensively to study static brain networks but may be limited in the study of rapidly changing brain connectivity during induction of or recovery from general anesthesia. Here we introduce a novel method to study the temporal evolution of network modules in the brain. We recorded multichannel electroencephalograms (EEG) from 18 surgical patients who underwent general anesthesia with either propofol (n = 9) or sevoflurane (n = 9). Time series data were used to reconstruct networks; each electroencephalographic channel was defined as a node and correlated activity between the channels was defined as a link. We analyzed the frequency of subgraphs in the network with a defined number of links; subgraphs with a high probability of occurrence were deemed network “backbones.” We analyzed the behavior of network backbones across consciousness, anesthetic induction, anesthetic maintenance, and two points of recovery. Constitutive, variable and state-specific backbones were identified across anesthetic state transitions. Brain networks derived from neurophysiologic data can be deconstructed into network backbones that change rapidly across states of consciousness. This technique enabled a granular description of network evolution over time. The concept of network backbones may facilitate graph-theoretical analysis of dynamically changing networks.

Dissociation of vegetative and minimally conscious patients based on brain operational architectonics: factor of etiology

Discrimination between patients in vegetative (VS) and minimally conscious state (MCS) is currently based upon the behavioral gold standard. Behavioral assessment remains equivocal and difficult to interpret as evidence for the presence or absence of consciousness, resulting in possible clinical misdiagnosis in such patients. Application of an operational architectonics (OA) strategy to electroencephalogram (EEG) analysis reveals that absence of consciousness in patients in VS is paralleled by significant impairment in overall EEG operational architecture compared to patients in MCS: neuronal assemblies become smaller, their life span shortened, and they became highly unstable and functionally disconnected (desynchronized). However, in a previous study, patients with different brain damage etiologies were intermixed. Therefore, the goal of the present study was to investigate whether the application of OA methodology to EEG could reliably dissociate patients in VS and MCS independent of brain damage etiology. We conclude that the observed EEG OA structure impairment in patients in VS and partial preservation in patients in MCS is a marker of consciousness/unconsciousness rather than physiological damage. Results of this study may have neuroscientific, clinical, and ethical implications.

A range of antiepileptic drugs do not affect the recovery of consciousness in vegetative and minimally conscious states

Since most antiepileptic drugs (AEDs) have cognitive effects, the aim of this study was to evaluate the influence of AED therapy on the recovery of consciousness in 103 consecutive patients in a vegetative or minimally conscious state (VS, MCS). The levels of cognitive functioning (LCF) score was retrospectively compared after a three-month period of rehabilitation between patients who were medicated (n=54) and patients who were not medicated (n=49) with AEDs. Mean LCF scores in AED-medicated and nonmedicated patients were 2.2±0.7 and 2.3±0.8 at admission and 3.8±2.2 and 3.7±2.1 after three months, respectively (p values>0.05). These results did not change when we compared patients with the same etiology separately, with the same disorder of consciousness only, or patients treated with only one or more than one AED. In conclusion, AEDs did not affect the recovery of consciousness in a large cohort of patients in a VS or MCS following an acute brain injury.

Prognostic Value of Resting-State Electroencephalography Structure in Disentangling Vegetative and Minimally Conscious States

Background. Patients in a vegetative state pose problems in diagnosis, prognosis, and treatment. Currently, no prognostic markers predict the chance of recovery, which has serious consequences, especially in end-of-life decision making. Objective. We aimed to assess an objective measurement of prognosis using advanced electroencephalography (EEG). Methods. EEG data (19 channels) were collected in 14 patients who were diagnosed to be persistently vegetative based on repeated clinical evaluations at 3 months following brain damage. EEG structure parameters (amplitude, duration, and variability within quasi-stationary segments, as well as the spatial synchrony between such segments and the strength of this synchrony) were used to predict recovery of consciousness 3 months later. Results. The number and strength of cortical functional connections between EEG segments were higher in patients who recovered consciousness ( P < .05 to P < .001) compared with those who did not recover. Linear regression analysis confirms that EEG structure parameters are capable of predicting ( P = .0025) recovery of consciousness 6 months postinjury, whereas the same analysis failed to significantly predict patient outcome based on aspects of their clinical history alone ( P = .629) or conventional EEG spectrum power ( P = .473). Conclusions. The result of this preliminary study demonstrates that structural strategy of EEG analysis is better suited for providing prognosis of consciousness recovery than existing methods of clinical assessment and of conventional EEG. Our results may be a starting point for developing reliable prognosticators in patients who are in a vegetative state, with the potential to improve their day-to-day management, quality of life, and access to early interventions.

DMN Operational Synchrony Relates to Self-Consciousness: Evidence from Patients in Vegetative and Minimally Conscious States

The default mode network (DMN) has been consistently activated across a wide variety of self-related tasks, leading to a proposal of the DMN’s role in self-related processing. Indeed, there is limited fMRI evidence that the functional connectivity within the DMN may underlie a phenomenon referred to as self-awareness. At the same time, none of the known studies have explicitly investigated neuronal functional interactions among brain areas that comprise the DMN as a function of self-consciousness loss. To fill this gap, EEG operational synchrony analysis [1, 2] was performed in patients with severe brain injuries in vegetative and minimally conscious states to study the strength of DMN operational synchrony as a function of self-consciousness expression. We demonstrated that the strength of DMN EEG operational synchrony was smallest or even absent in patients in vegetative state, intermediate in patients in minimally conscious state and highest in healthy fully self-conscious subjects. At the same time the process of ecoupling of operations performed by neuronal assemblies that comprise the DMN was highest in patients in vegetative state, intermediate in patients in minimally conscious state and minimal in healthy fully self-conscious subjects. The DMN’s frontal EEG operational module had the strongest decrease in operational synchrony strength as a function of selfconsciousness loss, when compared with the DMN’s posterior modules. Based on these results it is suggested that the strength of DMN functional connectivity could mediate the strength of self-consciousness expression. The observed alterations similarly occurred across EEG alpha, beta1 and beta2 frequency oscillations. Presented results suggest that the EEG operational synchrony within DMN may provide an objective and accurate measure for the assessment of signs of self-(un)consciousness in these challenging patient populations. This method therefore, may complement the current diagnostic procedures for patients with severe brain injuries and, hence, the planning of a rational rehabilitation intervention.