Differential diagnosis between Vegetative State and Minimally Conscious State is a challenging task that requires specific assessment scales, involvement of expert neuropsychologists or physicians and use of tailored stimuli for eliciting behavioural responses. Although misdiagnosis rate as high as 40% has been reported, no clear guidelines are available in literature on the optimal setting for assessment. The present study aims to analyse score differences in behavioural assessments of persons with disorders of consciousness (DOC) with or without family members and to determine whether the presence of caregivers could improve clinical accuracy in diagnostic evaluation. The research was conducted on 92 adults with DOC among 153 consecutive patients enrolled in the Coma Research Centre of the Neurological Institute C. Besta of Milan between January 2011 and May 2013. The results indicate that in almost half of the sample the scoring, thus the performance, observed with caregivers was better than without them. Furthermore, in 16% of the sample, when assessment was performed with caregivers there was a change in diagnosis, from Vegetative to Minimally Conscious State or from that to Severe Disability. Finally, statistical differences were found in relation to diagnosis between mean scores in the "visual function" Coma Recovery Scale revised's subscale obtained by raters plus caregiver and rates only assessment. This study demonstrates how the presence of caregivers can positively affect behavioural assessments of persons with DOC, thus contributing to the definition of the optimal setting for behavioural evaluation of patients, to decrease misdiagnosis rates.
Multimodal human brain mapping has been proposed as an integrated approach capable of improving the recognition of the cortical correlates of specific neurological functions. We used simultaneous EEG-fMRI (functional magnetic resonance imaging) and EEG-TDfNIRS (time domain functional near-infrared spectroscopy) recordings to compare different hemodynamic methods with changes in EEG in ten patients with progressive myoclonic epilepsy and 12 healthy controls. We evaluated O 2 Hb, HHb and Blood oxygen level-dependent (BOLD) changes and event-related desynchronization/synchronization (ERD/ERS) in the a and b bands of all of the subjects while they performed a simple motor task. The general linear model was used to obtain comparable fMRI and TDfNIRS activation maps. We also analyzed cortical thickness in order to evaluate any structural changes. In the patients, the TD-NIRS and fMRI data significantly correlated and showed a significant lessening of the increase in O 2 Hb and the decrease in BOLD. The post-movement b rebound was minimal or absent in patients. Cortical thickness was moderately reduced in the motor area of the patients and correlated with the reduction in the hemodynamic signals. The fMRI and TD-NIRS results were consistent, significantly correlated and showed smaller hemodynamic changes in the patients. This finding may be partially attributable to mild cortical thickening. However, cortical hyperexcitability, which is known to generate myoclonic jerks and probably accounts for the lack of EEG b-ERS, did not reflect any increased energy requirement. We hypothesize that this is due to a loss of inhibitory neuronal components that typically fire at high frequencies.
Background: Magneto-and Electro-encephalography record the electromagnetic field generated by neural currents with high temporal frequency and good spatial resolution, and are therefore well suited for source localization in the time and in the frequency domain. In particular, localization of the generators of neural oscillations is very important in the study of cognitive processes in the healthy and in the pathological brain. New method: We introduce the use of a Bayesian multi-dipole localization method in the frequency domain. Given the Fourier Transform of the data at one or multiple frequencies and/or trials, the algorithm approximates numerically the posterior distribution with Monte Carlo techniques. Results: We use synthetic data to show that the proposed method behaves well under a wide range of experimental conditions, including low signal-to-noise ratios and correlated sources. We use dipole clusters to mimic the effect of extended sources. In addition, we test the algorithm on real MEG data to confirm its feasibility. Comparison with existing method(s): Throughout the whole study, DICS (Dynamic Imaging of Coherent Sources) is used systematically as a benchmark. The two methods provide similar general pictures; the posterior distributions of the Bayesian approach contain much richer information at the price of a higher computational cost. Conclusions: The Bayesian method described in this paper represents a reliable approach for localization of multiple dipoles in the frequency domain.
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