Residual and compensatory changes of resting‐state EEG in successful recovery after moderate TBI

Purpose:

Even in years after recovery from moderate traumatic brain injury (moderate TBI), patients complain about residual cognitive impairment and fatigue. We hypothesized that non‐linear and linear resting‐state electroencephalography (rsEEG) features might also reflect neural underpinnings of these deficits.

Methods:

We analyzed a 10‐minute rsEEG in 77 moderate TBI‐survivors and 151 healthy volunteers after cognitive and psychological assessment. The rsEEG analysis included linear measures, such as power spectral density and peak alpha frequency, and non‐linear parameters such as Higuchi fractal dimension, envelope frequency, and Hjorth complexity.

Results:

The patients with moderate TBI had higher scores for fatigue and sleepiness and lower scores for mood and life satisfaction than controls. The behavioral test for directed attention showed a smaller and non‐significant between‐group difference. In rsEEG patterns, moderate TBI‐group had significantly higher deltaand theta‐rhythm power, which correlated with higher sleepiness and fatigue scores. The higher beta and lower alpha power were associated with a higher attention level in moderate TBI patients. Non‐linear rsEEG features were significantly higher in moderate TBI patients than in healthy controls but correlated with sleepiness and fatigue scores in both controls and patients.

Conclusion:

The rsEEG patterns may reflect compensatory processes supporting directed attention and residual effect of moderate TBI causing subjective fatigue in patients even after full physiological recovery.

EEG of patients in coma after traumatic brain injury reflects physical parameters of auditory stimulation but not its emotional content

PRIMARY OBJECTIVE

We aimed to investigate the origin of EEG response of patients in coma and after moderate TBI to emotional stimulation, whether they distinguish emotional content or only react to the physical features of an audio signal.

RESEARCH DESIGN

We registered EEG during continuous pleasant and unpleasant non-verbal stimulation and in rest. A total of 69 subjects participated in our study: healthy adults, conscious patients after moderate TBI and patients in coma after severe TBI. We analysed the distances between the stimuli according to EEG data and applied correlation analysis to the distances, acoustic parameters of stimuli, subjects' emotional assessment of the stimuli, GCS score and Doppler ultrasound data.

MAIN OUTCOMES AND RESULTS

The EEG response to the stimulation in patients in coma mostly reflects the physical parameters of the stimuli, and correlated with Doppler ultrasound data. The EEG of healthy adults reflects their psychological assessment of the stimuli. Patients after moderate TBI differentiate unpleasant stimuli well and pleasant stimuli poorly, they mainly consider pitch to cope with this task like healthy adults do.

CONCLUSIONS

The reactivity to the acoustic features of emotional stimulation in patients in coma should be investigated further as a marker of patients' recovery.

ABBREVIATIONS

TBI: traumatic brain injurym; TBI: moderate TBI; MCA: middle cerebral artery; GCS: Glasgow Coma Scale; M: mean; SD: standard deviation.

Nonlinear EEG parameters of emotional perception in patients with moderate traumatic brain injury, coma, stroke and schizophrenia

Objective

The aim of this study was to determine the EEG changes induced by emotional non-verbal sounds using nonlinear signals' features and also to examine the subjective emotional response in patients with different neurological and psychiatric disorders.

Methods

141 subjects participated in our study: patients after moderate TBI, patients in acute coma, patients after stroke, patients with schizophrenia and controls. 7 types of emotionally charged stimuli were presented. Non-comatose participants were asked to assess the levels of experienced emotions. We analyzed fractal dimension, signal's envelope parameters and Hjorth mobility and complexity.

Results

The Hjorth parameters were negatively correlated with irritation. The fractal dimension was positively correlated with arousal and empathy levels. The only presentation of laughter to post-stroke patients induced the reaction similar to the control group.

Conclusions

The results showed that the investigated nonlinear features of resting state EEG are quite group-specific and also specific to the emotional state.

Significance

The investigated features could serve to diagnose emotional impairments.

Emotion Recognition with Eigen Features of Frequency Band Activities Embedded in Induced Brain Oscillations Mediated by Affective Pictures

In this study, singular spectrum analysis (SSA) has been used for the first time in order to extract emotional features from well-defined electroencephalography (EEG) frequency band activities (BAs) so-called delta (0.5–4[Formula: see text]Hz), theta (4–8[Formula: see text]Hz), alpha (8–16[Formula: see text]Hz), beta (16–32[Formula: see text]Hz), gamma (32–64[Formula: see text]Hz). These five BAs were estimated by applying sixth-level multi-resolution wavelet decomposition (MRWD) with Daubechies wavelets (db-8) to single channel nonaveraged emotional EEG oscillations of 6 s for each scalp location over 16 recording sites (Fp1, Fp2, F3, F4, F7, F8, C3, C4, P3, P4, T3, T4, T5, T6, O1, O2). Every trial was mediated by different emotional stimuli which were selected from international affective picture system (IAPS) to induce emotional states such as pleasant (P), neutral (N), and unpleasant (UP). Largest principal components (PCs) of BAs were considered as emotional features and data mining approaches were used for the first time in order to classify both three different (P, N, UP) and two contrasting (P and UP) emotional states for 30 healthy controls. Emotional features extracted from gamma BAs (GBAs) for 16 recording sites provided the high classification accuracies of 87.1% and 100% for classification of three emotional states and two contrasting emotional states, respectively. In conclusion, we found the followings: (1) Eigenspectra of high frequency BAs in EEG are highly sensitive to emotional hemispheric activations, (2) emotional states are mostly mediated by GBA, (3) pleasant pictures induce the higher cortical activation in contrast to unpleasant pictures, (4) contrasting emotions induce opposite cortical activations, (5) cognitive activities are necessary for an emotion to occur.