Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Portnova GV

PROVIDER: S-EPMC7179336 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

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

Portnova Galina V GV Atanov Michael S MS

AIMS neuroscience 20181107 4

<h4>Objective</h4>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.<h4>Methods</h4>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-c ...[more]

PMID: 32341963

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Project description:BackgroundIt is not currently possible to predict which patients will develop chronic disorders of consciousness (DoC) after severe traumatic brain injury (TBI). Although the ascending arousal network (AAN) supports human consciousness, it is unknown which AAN pathways must be preserved for patients to recover consciousness.MethodsSixteen patients with acute traumatic coma and 16 matched healthy controls were scanned with high angular resolution diffusion imaging (HARDI). All patients recovered consciousness (Recovery Cohort). Nine were scanned longitudinally: first in the ICU (Acute), then at ≥5 months post-injury (Follow-up). Six separate patients with post-traumatic DoC were scanned ≥5 months post-injury (Chronic DoC Cohort). For each AAN pathway, we computed the median relative change in Acute-to-Follow-up Connectivity Probability (CP) in the Recovery Cohort. We then used Wilcoxon tests with Bonferroni correction to compare CP in each AAN pathway in the Recovery Cohort at Follow-up versus the Chronic DoC Cohort. In an exploratory analysis, we used principal component analysis (PCA) to determine whether linear combinations of AAN CP values could separate the Chronic DoC Cohort from the Recovery Cohort and the healthy controls.ResultsIn the Recovery Cohort, the largest relative AAN CP changes were in the brainstem-to-thalamus (median [IQR] = 0.7 [0.09, 0.9]) and forebrain-to-occipital lobe (-0.8 [-0.9, -0.8]) pathways. The AAN connections that differed in the cross-sectional analysis between the Recovery Cohort at Follow-up and the Chronic DoC Cohort included brainstem-to-hypothalamus (W = 53, PBonf = 0.02), brainstem-to-temporal lobe (W = 52, PBonf = 0.04), and thalamus-to-temporal lobe (W = 54, PBonf = 0.009). Plotting the first two principal components of AAN connectivity resulted in a linear separation of Chronic DoC patients from other study groups.ConclusionsWe provide evidence for a longitudinal increase in brainstem-thalamic connectivity during recovery of consciousness after traumatic coma. Cross-sectional analyses revealed that brainstem-hypothalamus, brainstem-temporal lobe, and thalamus-temporal lobe connectivity differed between patients who recovered consciousness and those with a chronic DoC. These observations provide the basis for further investigation into AAN connectivity as a biomarker for recovery of consciousness after traumatic coma.

Project description:OBJECTIVES:Recovery from coma might critically depend on the structural and functional integrity of frontoparietal networks. We aimed to measure this integrity in traumatic brain injury and anoxo-ischemic (cardiac arrest) coma patients by using an original multimodal MRI protocol. DESIGN:Prospective cohort study. SETTING:Three Intensive Critical Care Units affiliated to the University in Toulouse (France). PATIENTS:We longitudinally recruited 43 coma patients (Glasgow Coma Scale at the admission < 8; 29 cardiac arrest and 14 traumatic brain injury) and 34 age-matched healthy volunteers. Exclusion criteria were disorders of consciousness lasting more than 30 days and focal brain damage within the explored brain regions. Patient assessments were conducted at least 2 days (5?±?2 d) after complete withdrawal of sedation. All patients were followed up (Coma Recovery Scale-Revised) 3 months after acute brain injury. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Functional and structural MRI data were recorded, and the analysis was targeted on the posteromedial cortex, the medial prefrontal cortex, and the cingulum. Univariate analyses and machine learning techniques were used to assess diagnostic and predictive values. Coma patients displayed significantly lower medial prefrontal cortex-posteromedial cortex functional connectivity (area under the curve, 0.94; 95% CI, 0.93-0.95). Cardiac arrest patients showed specific structural disturbances within posteromedial cortex. Significant cingulum architectural disturbances were observed in traumatic brain injury patients. The machine learning medial prefrontal cortex-posteromedial cortex multimodal classifier had a significant predictive value (area under the curve, 0.96; 95% CI, 0.95-0.97), best combination of subregions that discriminates a binary outcome based on Coma Recovery Scale-Revised). CONCLUSIONS:This exploratory study suggests that frontoparietal functional disconnections are specifically observed in coma and their structural counterpart provides information about brain injury mechanisms. Multimodal MRI biomarkers of frontoparietal disconnection predict 3-month outcome in our sample. These findings suggest that fronto-parietal disconnection might be particularly relevant for coma outcome prediction and could inspire innovative precision medicine approaches.

Dataset Information

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

Objective

Methods

Results

Conclusions

Significance

Publications

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

Similar Datasets

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