Accurate outcome detection in neuro-rehabilitative settings is crucial for appropriate long-term rehabilitative decisions in patients with disorders of consciousness (DoC). EEG measures derived from high-density EEG can provide helpful information regarding diagnosis and recovery in DoC patients. However, the accuracy rate of EEG biomarkers to predict the clinical outcome in DoC patients is largely unknown. This study investigated the accuracy of psychophysiological biomarkers based on clinical EEG in predicting clinical outcomes in DoC patients. To this aim, we extracted a set of EEG biomarkers in 33 DoC patients with traumatic and nontraumatic etiologies and estimated their accuracy to discriminate patients’ etiologies and predict clinical outcomes 6 months after the injury. Machine learning reached an accuracy of 83.3% (sensitivity = 92.3%, specificity = 60%) with EEG-based functional connectivity predicting clinical outcome in nontraumatic patients. Furthermore, the combination of functional connectivity and dominant frequency in EEG activity best predicted clinical outcomes in traumatic patients with an accuracy of 80% (sensitivity = 85.7%, specificity = 71.4%). These results highlight the importance of functional connectivity in predicting recovery in DoC patients. Moreover, this study shows the high translational value of EEG biomarkers both in terms of feasibility and accuracy for the assessment of DoC.
Evaluation of consciousness needs to be supported by the evidence of brain activation during external stimulation in patients with unresponsive wakefulness syndrome (UWS). Assessment of patients should include techniques that do not depend on overt motor responses and allow an objective investigation of the spontaneous patterns of brain activity. In particular, electroencephalography (EEG) coherence allows to easily measure functional relationships between pairs of neocortical regions and seems to be closely correlated with cognitive or behavioral measures. Here, we show the contribution of higher order associative cortices of patients with disorder of consciousness (N = 26) in response to simple sensory stimuli, such as visual, auditory and noxious stimulation. In all stimulus modalities an increase of short-range parietal and long-range fronto-parietal coherences in gamma frequencies were seen in the controls and minimally conscious patients. By contrast, UWS patients showed no significant modifications in the EEG patterns after stimulation. Our results suggest that UWS patients can not activate associative cortical networks, suggesting a lack of information integration. In fact, fronto-parietal circuits result to be connectively disrupted, conversely to patients that exhibit some form of consciousness. In the light of this, EEG coherence can be considered a powerful tool to quantify the involvement of cognitive processing giving information about the integrity of fronto-parietal network. This measure can represent a new neurophysiological marker of unconsciousness and help in determining an accurate diagnosis and rehabilitative intervention in each patient.
Background
Left hemispatial neglect (LHN) is a neuropsychological syndrome often associated with right hemispheric stroke. Patients with LHN have difficulties in attending, responding, and consciously representing the right side of space. Various rehabilitation protocols have been proposed to reduce clinical symptoms related to LHN, using cognitive treatments, or on non-invasive brain stimulation. However, evidence of their benefit is still lacking; in particular, only a few studies focused on the efficacy of combining different approaches in the same patient.
Methods
In the present study, we present the SMART ATLAS trial (Stimolazione MAgnetica Ripetitiva Transcranica nell’ATtenzione LAteralizzata dopo Stroke), a multicenter, randomized, controlled trial with pre-test (baseline), post-test, and 12 weeks follow-up assessments based on a novel rehabilitation protocol based on the combination of brain stimulation and standard cognitive treatment. In particular, we will compare the efficacy of inhibitory repetitive-transcranial magnetic stimulation (r-TMS), applied over the left intact parietal cortex of LHN patients, followed by visual scanning treatment, in comparison with a placebo stimulation (SHAM control) followed by the same visual scanning treatment, on visuospatial symptoms and neurophysiological parameters of LHN in a population of stroke patients.
Discussion
Our trial results may provide scientific evidence of a new, relatively low-cost rehabilitation protocol for the treatment of LHN.
Trial registration
ClinicalTrials.gov NCT04080999. Registered on September 2019.
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