Computer Engineering Technology

In this study we explored the use of coherence and Granger causality (GC) to separate patients in minimally conscious state (MCS) from patients with severe neurocognitive disorders (SND) that show signs of awareness. We studied 16 patients, 7 MCS and 9 SND with age between 18 and 49 years. Three minutes of ongoing electroencephalographic (EEG) activity was obtained at rest from 19 standard scalp locations, while subjects were alert but kept their eyes closed. GC was formulated in terms of linear autoregressive models that predict the evolution of several EEG time series, each representing the activity of one channel. The entire network of causally connected brain areas can be summarized as a graph of incompletely connected nodes. The 19 channels were grouped into five gross anatomical regions, frontal, left and right temporal, central, and parieto-occipital, while data analysis was performed separately in each of the five classical EEG frequency bands, namely delta, theta, alpha, beta, and gamma. Our results showed that the SND group consistently formed a larger number of connections compared to the MCS group in all frequency bands. Additionally, the number of connections in the delta band (0.1-4 Hz) between the left temporal and parieto-occipital areas was significantly different (P \ 0.1%) in the two groups. Furthermore, in the beta band (12-18 Hz), the input to the frontal areas from all other cortical areas was also significantly different (P \ 0.1%) in the two groups. Finally, classification of the subjects into distinct groups using as features the number of connections within and between regions in all frequency bands resulted in 100% classification accuracy of all subjects. The results of this study suggest that analysis of brain connectivity networks based on GC can be a highly accurate approach for classifying subjects affected by severe traumatic brain injury.

How do humans learn complex visuomotor tasks with a strategic component? We explore this question in the context of the Naval Research Laboratories Navigation Task that is used for selecting and training future submarine pilots. About 50% of participants fail to achieve the desired competence level on the task, even after a large number of trials. A central question in this project is whether we can analyze learning failures rapidly enough to intervene during training. To this end, we set out to identify a neural signature of strategy formulation by adopting a system-of-systems approach to dynamically track the learning state of a subject using measurements of brain activity and coordinated visuomotor actions throughout the learning process. We analyzed the spatiotemporal profiles of brain activation using a coherence measure and interpreted them based on the visuomotor performance data. Our results show the presence of long-range synchronies in the gamma band of brain activity in subjects who successfully formulate a strategy for the task and suggest a tight cooperation between occipital and frontal brain regions. These long-range synchronies are absent in lower frequencies. Subjects who lack this pattern fail to devise an appropriate strategy, a fact confirmed by the analysis of their visuomotor performance data. The absence or presence of long-range synchronies in the gamma band can be detected fairly early during the learning process and, therefore, our method can be used to identify learning difficulties that would require appropriate intervention based on neural signatures of strategy formulation.

En face adaptive optics scanning laser ophthalmoscope (AOSLO) images of the anterior lamina cribrosa surface (ALCS) represent a 2D projected view of a 3D laminar surface. Using spectral domain optical coherence tomography images acquired in living monkey eyes, a thin plate spline was used to model the ALCS in 3D. The 2D AOSLO images were registered and projected onto the 3D surface that was then tessellated into a triangular mesh to characterize differences in pore geometry between 2D and 3D images. Following 3D transformation of the anterior laminar surface in 11 normal eyes, mean pore area increased by 5.1 ± 2.0% with a minimal change in pore elongation (mean change = 0.0 ± 0.2%). These small changes were due to the relatively flat laminar surfaces inherent in normal eyes (mean radius of curvature = 3.0 ± 0.5 mm). The mean increase in pore area was larger following 3D transformation in 4 glaucomatous eyes (16.2 ± 6.0%) due to their more steeply curved laminar surfaces (mean radius...

In this study, we compared the brain activation profiles obtained from resting state Magnetoencephalographic (MEG) activity in 15 dyslexic patients with the profiles of 15 normal controls, using power spectral density (PSD) analysis. We first estimated intracranial dipolar MEG sources on a dense grid on the cortical surface and then projected these sources on a standardized atlas with 68 regions of interest (ROIs). Averaging the PSD values of all sources in each ROI across all control subjects resulted in a normative database that was used to convert the PSD values of dyslexic patients into z-scores in eight distinct frequency bands. We found that dyslexic patients exhibited statistically significant overactivation in the delta band (0.1-4 Hz) in the right temporal (entorhinal and insula), left inferior frontal (Broca's area), and right inferior frontal regions. Overactivation may be interpreted as a compensatory mechanism for reading characterizing dyslexic patients. These find...