Application of nonlinear dynamics analysis in assessing unconsciousness: A preliminary study

Altered resting state effective connectivity in long-standing vegetative state patients: an EEG study

OBJECTIVE

Recent evidence mainly based on hemodynamic measures suggests that the impairment of functional connections between different brain areas may help to clarify the neuronal dysfunction occurring in patients with disorders of consciousness (DOC). The aim of this study was to evaluate effective EEG connectivity in a cohort of 18 patients in a chronic vegetative state (VS) observed years after the occurrence of hypoxic (eight) and traumatic or hemorrhagic brain insult.

METHODS

we analysed the EEG signals recorded under resting conditions using a frequency domain linear index of connectivity (partial directed coherence: PDC) estimated from a multivariate autoregressive model. The results were compared with those obtained in ten healthy controls.

RESULTS

Our findings indicated significant connectivity changes in EEG activities in delta and alpha bands. The VS patients showed a significant and widespread decrease in delta band connectivity, whereas the alpha activity was hyper-connected in the central and posterior cortical regions.

CONCLUSION

These changes suggest the occurrence of severe circuitry derangements probably due to the loose control of the subcortical connections. The alpha hyper-synchronisation may be due to simplified networks mainly involving the short-range connections between intrinsically oscillatory cortical neurons that generate aberrant EEG alpha sources. This increased connectivity may be interpreted as a reduction in information capacity, implying an increasing prevalence of stereotypic activity patterns.

SIGNIFICANCE

Our observations suggest a remarkable rearrangement of connectivity in patients with long-standing VS. We hypothesize that in persistent VS, after a first period characterized by a breakdown of cortical connectivity, neurodegenerative processes, largely independent from the type of initial insult, lead to cortex de-afferentation and to a severe reduction of possible cortical activity patterns and states.

Multiscale cross-approximate entropy analysis as a measure of complexity among the aged and diabetic

Complex fluctuations within physiological signals can be used to evaluate the health of the human body. This study recruited four groups of subjects: young healthy subjects (Group 1, n = 32), healthy upper middle-aged subjects (Group 2, n = 36), subjects with well-controlled type 2 diabetes (Group 3, n = 31), and subjects with poorly controlled type 2 diabetes (Group 4, n = 24). Data acquisition for each participant lasted 30 minutes. We obtained data related to consecutive time series with R-R interval (RRI) and pulse transit time (PTT). Using multiscale cross-approximate entropy (MCE), we quantified the complexity between the two series and thereby differentiated the influence of age and diabetes on the complexity of physiological signals. This study used MCE in the quantification of complexity between RRI and PTT time series. We observed changes in the influences of age and disease on the coupling effects between the heart and blood vessels in the cardiovascular system, which reduced the complexity between RRI and PTT series.

EEG complexity drug-induced changes in disorders of consciousness: a preliminary report

The goal of this work is to investigate EEG (ElectroEncephaloGram) dynamics after drug intake in patients being in states of Disorders Of Consciousness (DOC) after brain injury. Four patients were involved in the study. All the patients exhibit cerebral lesions located in the same anatomical region. Two nonlinear indexes, such as Lempel-Ziv Complexity (LZC) and Approximate Entropy (ApEn), along with power spectra, were calculated for EEG signals gathered from electrodes placed on both injured and non-injured regions. Experimental results show that after drug administration the two nonlinear indexes calculated from EEG taken from injured regions increase (p < 0.001) while power spectra decrease or remain unchanged. These results do not pretend to draw conclusions about consciousness level either suggest promising therapeutical treatments, but represent only an experimental evidence about the change in the EEG complexity after drug administration.

Entropy analysis of tri-axial leg acceleration signal waveforms for measurement of decrease of physiological variability in human gait

Disease-related and senescent decrease of physiological variability in biological time-series outputs (e.g., heart rate) has drawn increasing attention as a potential new type of biomarker. In this paradigm, measurement of variability in periodic motion may enable quantitative evaluation of functional limitation in people with musculoskeletal disorders. A novel technique to measure variability of leg motion patterns during level walking was used to study 52 adults with symptomatic knee osteoarthritis (OA), and 57 asymptomatic control subjects over a wide range of age (20-79 years). The hypothesis was that cycle-to-cycle variability in leg motion patterns, indexed by tri-axial acceleration signal entropy, would be lower in those with greater age or with knee symptoms. Leg motions were assessed using portable inertial monitors attached bilaterally just above each ankle. The tri-axial acceleration data were analyzed using a nonlinear variability measurement tool designated as Sample Entropy (SampEn). SampEn data for asymptomatic subjects exhibited a significant negative correlation (r = -0.287, p = 0.0306) with greater age. OA subjects had significantly lower SampEn values (p = 0.0002) than did age-matched asymptomatic subjects who walked at equivalent velocity. This approach holds promise as a basis for valid, inexpensive, and convenient objective evaluation of limitations in human gait function.

Cortical source of blink-related delta oscillations and their correlation with levels of consciousness

Recently, blink-related delta oscillations (delta BROs) have been observed in healthy subjects during spontaneous blinking at rest. Delta BROs have been linked with continuous gathering of information from the surrounding environment, which is classically attributed to the precuneus. Furthermore, fMRI studies have shown that precuneal activity is reduced or missing when consciousness is low or absent. We therefore hypothesized that the source of delta BROs in healthy subjects could be located in the precuneus and that delta BROs could be absent or reduced in patients with disorders of consciousness (DOC). To test these hypotheses, electroencephalographic (EEG) activity at rest was recorded in 12 healthy controls and nine patients with DOC (four vegetative states, and five minimally conscious states). Three-second-lasting EEG epochs centred on each blink instance were analyzed in both time- (BROs) and frequency domains (event-related spectral perturbation or ERSP and intertrial coherence or ITC). Cortical sources of the maximum blink-related delta power, corresponding to the positive peak of the delta BROs, were estimated by standardized Low Resolution Electromagnetic Tomography. In control subjects, as expected, the source of delta BROs was located in the precuneus, whereas in DOC patients, delta BROs were not recognizable and no precuneal localization was possible. Furthermore, we observed a direct relationship between spectral indexes and levels of cognitive functioning in all subjects participating in the study. This reinforces the hypothesis that delta BROs reflect neural processes linked with awareness of the self and of the environment.

Application of approximate entropy on dynamic characteristics of epileptic absence seizure

Electroencephalogram signals are time-varying complex electrophysiological signals. Existing studies show that approximate entropy, which is a nonlinear dynamics index, is not an ideal method for electroencephalogram analysis. Clinical electroencephalogram measurements usually contain electrical interference signals, creating additional challenges in terms of maintaining robustness of the analytic methods. There is an urgent need for a novel method of nonlinear dynamical analysis of the electroencephalogram that can characterize seizure-related changes in cerebral dynamics. The aim of this paper was to study the fluctuations of approximate entropy in preictal, ictal, and postictal electroencephalogram signals from a patient with absence seizures, and to improve the algorithm used to calculate the approximate entropy. The approximate entropy algorithm, especially our modified version, could accurately describe the dynamical changes of the brain during absence seizures. We could also demonstrate that the complexity of the brain was greater in the normal state than in the ictal state. The fluctuations of the approximate entropy before epileptic seizures observed in this study can form a good basis for further study on the prediction of seizures with nonlinear dynamics.

Life or death: prognostic value of a resting EEG with regards to survival in patients in vegetative and minimally conscious States

OBJECTIVE

To investigate the potentially prognostic value of a resting state electroencephalogram (EEG) with regards to the clinical outcome from vegetative and minimally conscious states (VS and MCS) in terms of survival six months after a brain injury.

METHODS

We quantified a dynamic repertoire of EEG oscillations in resting condition with eyes closed in patients in VS and MCS. The exact composition of EEG oscillations was assessed by analysing the probability-classification of short-term EEG spectral patterns.

RESULTS

Results demonstrated that (a) the diversity and the variability of EEG for Non-Survivors were significantly lower than for Survivors; and (b) a higher probability of mostly delta and slow-theta oscillations occurring either alone or in combination were found during the first assessment for patients with a bad outcome (i.e., those who died) within six months of an injury compared to patients who survived. At the same time, patients with a good outcome (i.e., those who survived) after six months post-injury had a higher probability of mostly fast-theta and alpha oscillations occurring either alone or in combination during the first assessment when compared to patients who died within six months of an injury.

CONCLUSIONS

Resting state EEGs properly analysed may have a potentially prognostic value with regards to the outcome from VS or MCS in terms of survival six months after a brain injury.

SIGNIFICANCE

This work may have implications for clinical care, rehabilitative programmes and medical-legal decisions for patients with impaired consciousness states after being in a coma due to acute brain injuries.

Measuring interconnection of the residual cortical functional islands in persistent vegetative state and minimal conscious state with EEG nonlinear analysis

OBJECTIVES

The aim of the study is to investigate the cortical response to painful and auditory stimuli for subjects in persistent vegetative state (PVS) and minimal conscious state (MCS), and measure the interconnection of the residual cortical functional islands with electroencephalographic (EEG) nonlinear dynamic analysis (NDA).

METHODS

Thirty PVS subjects, 20 MCS subjects and 30 subjects in normal conscious state (NCS) were involved in the study. EEG was recorded under three conditions: eyes closed, auditory stimuli and painful stimuli. EEG nonlinear index of cross-approximate entropy (C-ApEn) was calculated for all subjects.

RESULTS

Interconnection of local and distant cortical networks of patients in PVS was generally suppressed, and painful or auditory stimulation could hardly cause any activation of associative cortices. Instead, interconnection of local cortical networks of patients in MCS improved significantly. The only significant difference with the NCS existed in the unaffected distant cortical networks.

CONCLUSIONS

Interconnection of local and distant cortical networks in MCS is superior to that of PVS. NDA could measure interconnection of the residual cortical functional islands with associative cortices in the unconscious patients.

SIGNIFICANCE

NDA can characterise the interconnection of cortical networks for the unconscious state and provide some information of unconsciousness at the awareness level.